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Volume 11
Issue 6
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Micromachines, Volume 11, Issue 6 (June 2020) – 87 articles

Cover Story (view full-size image): In this study, an alternative fan-out wafer-level packaging (FOWLP) concept implementing additively manufactured redistribution layers (RDLs) for capacitive micromachined ultrasound transducer (CMUT) array packaging was proposed. The printed RDLs served as an interconnect between capacitive microphones and speakers, operating in the ultrasonic domain, with corresponding application-specific integrated circuits (ASICs), which allow features such as touchless activation or control using gestures. View this paper
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12 pages, 2141 KiB  
Article
Highly Localized Enrichment of Trypanosoma brucei Parasites Using Dielectrophoresis
by Devin Keck, Callie Stuart, Josie Duncan, Emily Gullette and Rodrigo Martinez-Duarte
Micromachines 2020, 11(6), 625; https://doi.org/10.3390/mi11060625 - 26 Jun 2020
Cited by 8 | Viewed by 3574
Abstract
Human African trypanosomiasis (HAT), also known as sleeping sickness, is a vector-borne neglected tropical disease endemic to rural sub-Saharan Africa. Current methods of early detection in the affected rural communities generally begin with general screening using the card agglutination test for trypanosomiasis (CATT), [...] Read more.
Human African trypanosomiasis (HAT), also known as sleeping sickness, is a vector-borne neglected tropical disease endemic to rural sub-Saharan Africa. Current methods of early detection in the affected rural communities generally begin with general screening using the card agglutination test for trypanosomiasis (CATT), a serological test. However, the gold standard for confirmation of trypanosomiasis remains the direct observation of the causative parasite, Trypanosoma brucei. Here, we present the use of dielectrophoresis (DEP) to enrich T. brucei parasites in specific locations to facilitate their identification in a future diagnostic assay. DEP refers to physical movement that can be selectively induced on the parasites when exposing them to electric field gradients of specific magnitude, phase and frequency. The long-term goal of our work is to use DEP to selectively trap and enrich T. brucei in specific locations while eluting all other cells in a sample. This would allow for a diagnostic test that enables the user to characterize the presence of parasites in specific locations determined a priori instead of relying on scanning a sample. In the work presented here, we report the characterization of the conditions that lead to high enrichment, 780% in 50 s, of the parasite in specific locations using an array of titanium microelectrodes. Full article
(This article belongs to the Special Issue Micromachines for Dielectrophoresis)
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Figure 1
<p>Fabrication of Ti electrodes: (<b>A</b>) A six-inch silicon substrate was descummed with oxygen plasma treatment at 20 uTorr. (<b>B</b>) LOR resist was spin coated at 2000 rpm for 45 s on to the silicon substrate and a soft bake was performed at 150 °C for 150 s. (<b>C</b>) AZ701 resist was spin coated at 3000 rpm for 45 s on top of the LOR resist layer and a soft bake was performed at 110 °C for 75 s. (<b>D</b>) A Quintel Ultra i-line Series machine was used to pattern the resist layers using UV light with λ = 365 nm at an intensity of 6 mW/cm<sup>2</sup> for 20 s. Pattern development was performed via immersion in a 2.3% tetramethylammonium hydroxide/97.7% water bath (<b>E</b>). The patterned silicon substrate was transferred to a CCS CA-40 E-beam Evaporator to deposit 350 nm of Ti. (<b>F</b>) Lastly, the wafer was immersed in NMP (1-methyl-2-pyrrolidone) to dissolve the AZ and LOR layers and effectively lift-off Ti from undesired regions of the substrate (<a href="#micromachines-11-00625-f001" class="html-fig">Figure 1</a>F). (<b>G</b>) Conceptual schematic of the cross section of an experimental device. (<b>H</b>) Experimental device and details of electrode dimensions and predefined regions of interest surrounding a single semicircular electrode.</p> Full article ">Figure 2
<p>The total clump area of <span class="html-italic">Trypanosoma brucei</span> measured in different samples featuring a standard dielectrophoresis (DEP) experimental medium (120 µS/cm) and in experimental media with increasing electrical conductivity. The control was a sample of <span class="html-italic">T. brucei</span> in their standard culture media. An experimental medium with electrical conductivity of 504 µS/cm was chosen as a compromise between maintaining a suspension of individual parasites and a conductivity value that can lead to a strong positive DEP response.</p> Full article ">Figure 3
<p>Modeling of the electric field <b><span class="html-italic">E</span></b> for an array of titanium electrodes (white geometries) polarized using different voltages: (<b>A</b>) 20 V<sub>pp</sub> (<b>B</b>) 15 V<sub>pp</sub> (<b>C</b>) 10 V<sub>pp</sub> and (<b>D</b>) 5 V<sub>pp</sub>. The modeled media around electrodes was water with an electrical conductivity of 504 µS/cm. As expected, the magnitude of the electric field increases proportionally to the magnitude of the polarizing voltage. A magnitude of <b><span class="html-italic">E</span></b> &lt; 10<sup>5</sup> V/m is desired to minimize the risk of electrically lysing the parasites. (<b>E</b>) Modeling of ▽ <b><span class="html-italic">E</span></b><sup>2</sup> in an array of titanium electrodes (white geometries) polarized using 5 V<sub>pp</sub>. The modeled media around electrodes was water with an electrical conductivity of 504 µS/cm. If the parasites experience a positive DEP force, they are expected to migrate to the regions of highest ▽ <b><span class="html-italic">E</span></b><sup>2</sup>, shown as orange–red in the figure.</p> Full article ">Figure 4
<p>(<b>A</b>) Characterization of the DEP response of <span class="html-italic">T. brucei</span> across a broad frequency range, 100 kHz to 20 MHz. Dark blue bars represent the standard deviation between experiments (<span class="html-italic">n</span> = 3). (<b>B</b>) <span class="html-italic">T. brucei</span> cultured at 29 °C in 5% CO<sub>2</sub> in SDM-79 media with a target density between 5 × 10<sup>5</sup> and 1 × 10<sup>7</sup> cell/mL. Courtesy of Christina Wilkinson and James Morris.</p> Full article ">Figure 5
<p>(<b>A</b>) Regional enrichment study of parasites from time t = 0 to t = 50 s for four predefined regions of interest shown in <a href="#micromachines-11-00625-f001" class="html-fig">Figure 1</a>H. All enrichment experiments were performed at a frequency of 750 kHz, as such frequency yields the strongest positive DEP response of <span class="html-italic">T. brucei</span> under the conditions studied in this work. (<b>B</b>) Single electrode at t = 0 illustrating low attachment of parasites to electrode edges. (<b>C</b>) Single electrode at t = 50 illustrating high attachment of parasites to electrode edges, particularly in regions 3 and 4 (dashed rectangles).</p> Full article ">
28 pages, 2745 KiB  
Review
Recent Developments in Ozone Sensor Technology for Medical Applications
by Lisa Petani, Liane Koker, Janina Herrmann, Veit Hagenmeyer, Ulrich Gengenbach and Christian Pylatiuk
Micromachines 2020, 11(6), 624; https://doi.org/10.3390/mi11060624 - 26 Jun 2020
Cited by 23 | Viewed by 5418
Abstract
There is increasing interest in the utilisation of medical gases, such as ozone, for the treatment of herniated disks, peripheral artery diseases, and chronic wounds, and for dentistry. Currently, the in situ measurement of the dissolved ozone concentration during the medical procedures in [...] Read more.
There is increasing interest in the utilisation of medical gases, such as ozone, for the treatment of herniated disks, peripheral artery diseases, and chronic wounds, and for dentistry. Currently, the in situ measurement of the dissolved ozone concentration during the medical procedures in human bodily liquids and tissues is not possible. Further research is necessary to enable the integration of ozone sensors in medical and bioanalytical devices. In the present review, we report selected recent developments in ozone sensor technology (2016–2020). The sensors are subdivided into ozone gas sensors and dissolved ozone sensors. The focus thereby lies upon amperometric and impedimetric as well as optical measurement methods. The progress made in various areas—such as measurement temperature, measurement range, response time, and recovery time—is presented. As inkjet-printing is a new promising technology for embedding sensors in medical and bioanalytical devices, the present review includes a brief overview of the current approaches of inkjet-printed ozone sensors. Full article
(This article belongs to the Special Issue Deformable Bioelectronics Based on Functional Micro/nanomaterials)
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<p>Schematic of possible applications for ozone treatment in healthcare. The applications reach from disk herniation and osteoarthritis, to coronary and peripheral artery disease, madelung disease, dyslipidemia, cholesterol embolism, and dentistry.</p> Full article ">Figure 2
<p>Number of publications featuring ozone sensors. Source: Scopus. Data extracted on 12 March 2020. All documents containing <span class="html-italic">ozone</span> and <span class="html-italic">sensor</span> were considered in the query and these documents were subdivided into the respective years.</p> Full article ">Figure 3
<p>Schematic of a basic sensor structure, which consists of a membrane, sensing material, substrate, and encapsulation. The materials are employed in regard to integrate the sensor in medical and bioanalytical devices.</p> Full article ">Figure 4
<p>Schematic of an amperometric sensor. Between the working and reference electrode, a constant voltage is applied. The current, measured at the working electrode, changes when ozone is present in the measurement substance.</p> Full article ">Figure 5
<p>Schematic of an impedimetric sensor. (<b>a</b>) The bottom, side, and top views of the impedimetric sensor. (<b>b</b>) An expanded view of the sensor. Resistance Ω of the sensing material changes when ozone is present in the measurement substance.</p> Full article ">Figure 6
<p>Schematic of an optical absorption sensor. The measurement method is based on measuring the light absorption of the measurement substance that is sent out by emitting diodes and detected by a photosensor.</p> Full article ">Figure 7
<p>Schematic of typical fabrication methods for ozone sensors. The substrate is shown in blue and the applied ink or thin film material in red. (<b>a</b>) The spin-coating process. (<b>b</b>) A schematic of dip-coating/immersion. (<b>c</b>) The screen-printing process. (<b>d</b>) The UV photolithography process. (<b>e</b>) The spray-coating/spray pyrolysis process. (<b>f</b>) The inkjet-printing process.</p> Full article ">
11 pages, 3853 KiB  
Article
Development of a High-Density Piezoelectric Micromachined Ultrasonic Transducer Array Based on Patterned Aluminum Nitride Thin Film
by Eunjung Shin, Hong Goo Yeo, Ara Yeon, Changzhu Jin, Wonki Park, Sung-Chul Lee and Hongsoo Choi
Micromachines 2020, 11(6), 623; https://doi.org/10.3390/mi11060623 - 26 Jun 2020
Cited by 30 | Viewed by 5423
Abstract
This study presents the fabrication and characterization of a piezoelectric micromachined ultrasonic transducer (pMUT; radius: 40 µm) using a patterned aluminum nitride (AlN) thin film as the active piezoelectric material. A 20 × 20 array of pMUTs using a 1 µm thick AlN [...] Read more.
This study presents the fabrication and characterization of a piezoelectric micromachined ultrasonic transducer (pMUT; radius: 40 µm) using a patterned aluminum nitride (AlN) thin film as the active piezoelectric material. A 20 × 20 array of pMUTs using a 1 µm thick AlN thin film was designed and fabricated on a 2 × 2 mm2 footprint for a high fill factor. Based on the electrical impedance and phase of the pMUT array, the electromechanical coefficient was ~1.7% at the average resonant frequency of 2.82 MHz in air. Dynamic displacement of the pMUT surface was characterized by scanning laser Doppler vibrometry. The pressure output while immersed in water was 19.79 kPa when calculated based on the peak displacement at the resonant frequency. The proposed AlN pMUT array has potential applications in biomedical sensing for healthcare, medical imaging, and biometrics. Full article
(This article belongs to the Special Issue Selected Papers from the ICAE 2019)
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<p>Top view and cross-sectional schematic illustrations of an AlN pMUT element.</p> Full article ">Figure 2
<p>Fabrication process of the AlN pMUT array; (<b>a</b>) Diffusion of a silicon oxide layer. (<b>b</b>) Deposition of seed layer (AlN), bottom electrode (Mo) and AlN piezoelectric layer. (<b>c</b>) Deposition and patterning of top electrode (Au). (<b>d</b>) Patterning of AlN layer. (<b>e</b>) Deposition and patterning of connecting layer (Au) for bottom electrode. (<b>f</b>) Deposition and patterning of silicon oxide layer. (<b>g</b>) Deposition and patterning of Au-Sn bumps. (<b>h</b>) Patterning of silicon oxide using hard mask (Al) on backside. (<b>i</b>) Deep silicon etching on backside to release the membrane.</p> Full article ">Figure 3
<p>Photograph of the fabricated 20 × 20 AlN pMUT array (400 elements) beside a 10-won Korean coin.</p> Full article ">Figure 4
<p>Fabricated (<b>a</b>) single-element and (<b>b</b>) 20 × 20 array of AlN pMUTs.</p> Full article ">Figure 5
<p>Scanning electron microscope images of the fabricated AlN pMUT array. (<b>a</b>) Top view and (<b>b</b>) cross-sectional view.</p> Full article ">Figure 6
<p>Cross-sectional scanning electron microscope images of the membrane structure (left image) and magnified device multilayer (right image) of the AlN pMUT element.</p> Full article ">Figure 7
<p>A rocking curve of the sputtered AlN film.</p> Full article ">Figure 8
<p>Impedance and phase of an AlN pMUT element of the 20 × 20 array.</p> Full article ">Figure 9
<p>Mechanical displacement of the fabricated AlN pMUT device. (<b>a</b>) Single and (<b>b</b>) array pMUT with periodic chirp input.</p> Full article ">Figure 10
<p>Mechanical displacement of the fabricated AlN pMUT device. (<b>a</b>) Single and (<b>b</b>) array pMUT with sinusoidal input.</p> Full article ">
13 pages, 1470 KiB  
Article
Efficient Acceleration of Stencil Applications through In-Memory Computing
by Hasan Erdem Yantır, Ahmed M. Eltawil and Khaled N. Salama
Micromachines 2020, 11(6), 622; https://doi.org/10.3390/mi11060622 - 26 Jun 2020
Cited by 8 | Viewed by 3655
Abstract
The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is increasing rapidly, especially after the era of [...] Read more.
The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is increasing rapidly, especially after the era of big data and artificial intelligence. This fact forces new constraints in computer architecture design towards more data-centric principles. Therefore, new paradigms such as in-memory and near-memory processors have begun to emerge to counteract the memory bottleneck by bringing memory closer to computation or integrating them. Associative processors are a promising candidate for in-memory computation, which combines the processor and memory in the same location to alleviate the memory bottleneck. One of the applications that need iterative processing of a huge amount of data is stencil codes. Considering this feature, associative processors can provide a paramount advantage for stencil codes. For demonstration, two in-memory associative processor architectures for 2D stencil codes are proposed, implemented by both emerging memristor and traditional SRAM technologies. The proposed architecture achieves a promising efficiency for a variety of stencil applications and thus proves its applicability for scientific stencil computing. Full article
(This article belongs to the Special Issue Progress of Emerging Hardware Development for Post-Moore’s Computing)
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<p>Architecture of an associative in-memory processor with SRAM and ReRAM based cell types.</p> Full article ">Figure 2
<p>The sequence of compare and write operations are shown for a complete vector addition operation on 2-bit, 4 × 1 vector pairs of A (column 1-0), and B (column 3-2). The highlighted lookup table (LUT) entry shows the applied key values to the corresponding content addressable memory (CAM) columns specified by the mask register, and the arrows indicate the flow.</p> Full article ">Figure 3
<p>Three types of 2D stencil codes (Laplace, 5-point, and 9-point) together with their corresponding equations and computation patterns.</p> Full article ">Figure 4
<p>2D Stencil implementation (5-point iteration) on the associative processor (AP).</p> Full article ">Figure 5
<p>Peak signal-to-noise ratio (PSNR) with respect to the iteration number during various stencil operations on 64 × 64 matrices.</p> Full article ">Figure 6
<p>Single iteration run times of three stencil codes with variable array sizes of nxm where n is set as 4096 and m is between 1 K and 64 K.</p> Full article ">Figure 7
<p>Single iteration run times of three stencil codes with variable array size of nxm where n = m.</p> Full article ">Figure 8
<p>Results of approximate stencil code on the AP.</p> Full article ">
17 pages, 6565 KiB  
Article
A mm-Sized Free-Floating Wireless Implantable Opto-Electro Stimulation Device
by Yaoyao Jia, Yan Gong, Arthur Weber, Wen Li and Maysam Ghovanloo
Micromachines 2020, 11(6), 621; https://doi.org/10.3390/mi11060621 - 25 Jun 2020
Cited by 4 | Viewed by 5934
Abstract
Towards a distributed neural interface, consisting of multiple miniaturized implants, for interfacing with large-scale neuronal ensembles over large brain areas, this paper presents a mm-sized free-floating wirelessly-powered implantable opto-electro stimulation (FF-WIOS2) device equipped with 16-ch optical and 4-ch electrical stimulation for reconfigurable neuromodulation. [...] Read more.
Towards a distributed neural interface, consisting of multiple miniaturized implants, for interfacing with large-scale neuronal ensembles over large brain areas, this paper presents a mm-sized free-floating wirelessly-powered implantable opto-electro stimulation (FF-WIOS2) device equipped with 16-ch optical and 4-ch electrical stimulation for reconfigurable neuromodulation. The FF-WIOS2 is wirelessly powered and controlled through a 3-coil inductive link at 60 MHz. The FF-WIOS2 receives stimulation parameters via on-off keying (OOK) while sending its rectified voltage information to an external headstage for closed-loop power control (CLPC) via load-shift-keying (LSK). The FF-WIOS2 system-on-chip (SoC), fabricated in a 0.35-µm standard CMOS process, employs switched-capacitor-based stimulation (SCS) architecture to provide large instantaneous current needed for surpassing the optical stimulation threshold. The SCS charger charges an off-chip capacitor up to 5 V at 37% efficiency. At the onset of stimulation, the capacitor delivers charge with peak current in 1.7–12 mA range to a micro-LED (µLED) array for optical stimulation or 100–700 μA range to a micro-electrode array (MEA) for biphasic electrical stimulation. Active and passive charge balancing circuits are activated in electrical stimulation mode to ensure stimulation safety. In vivo experiments conducted on three anesthetized rats verified the efficacy of the two stimulation mechanisms. The proposed FF-WIOS2 is potentially a reconfigurable tool for performing untethered neuromodulation. Full article
(This article belongs to the Special Issue Implantable Microdevices, Volume II)
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<p>Conceptual view of the system setup for operating multiple mm-sized free-floating wirelessly-powered implantable opto-electro stimulation (FF-WIOS2) devices, distributed on a freely moving rat brain.</p> Full article ">Figure 2
<p>Block diagram of the FF-WIOS2 system-on-chip (SoC) architecture.</p> Full article ">Figure 3
<p>Schematic diagram of (<b>a</b>) the voltage doubler with built-in charger and the cap-less LDO, (<b>b</b>) the clock generator for the timing of stimulation and charging functions, (<b>c</b>) the OOK demodulator and PPM-CDR in forward data telemetry, (<b>d</b>) the LSK back telemetry, (<b>e</b>) the stimulation driver in H-bridge configuration, and (<b>f</b>) the active charge balancing (CB) circuit.</p> Full article ">Figure 4
<p>(<b>a</b>) In vitro system setup with a close-up view of the FF-WIOS2 device. (<b>b</b>) The fabricated FF-WIOS2 SoC micrograph.</p> Full article ">Figure 5
<p>Block diagram of the headstage.</p> Full article ">Figure 6
<p>(<b>a</b>) In vivo experimental setup with its (<b>b</b>) block diagram.</p> Full article ">Figure 7
<p>Transient waveforms of the power management block at starting up.</p> Full article ">Figure 8
<p>Measured results of forward data telemetry.</p> Full article ">Figure 9
<p>(<b>a</b>) Measured optical stimulation waveforms. (<b>b</b>) Measured µLED current at different stimulation current settings. (<b>c</b>) Measured light intensity as a function of the μLED current.</p> Full article ">Figure 10
<p>Measured electrical stimulation waveforms with active charge balancing.</p> Full article ">Figure 11
<p>Measured waveforms under CLPC operation, when moving the headstage to change the distance between <span class="html-italic">L</span><sub>Tx</sub> and <span class="html-italic">L</span><sub>Res</sub>, <span class="html-italic">D</span>.</p> Full article ">Figure 12
<p>Power consumption of each block in the FF-WIOS2 device when applying (<b>a</b>) electrical stimulation and (<b>b</b>) optical stimulation.</p> Full article ">Figure 13
<p>LFP analysis in terms of (<b>a</b>) amplitude variation and (<b>b</b>) normalized PSD with maximum and minimum optical stimulation.</p> Full article ">Figure 14
<p>C-Fos expression in the left (stimulated) vs. right (control) V1 lobes.</p> Full article ">Figure 15
<p>LFP analysis in terms of (<b>a</b>) amplitude variation and (<b>b</b>) normalized PSD with maximum and minimum electrical stimulation.</p> Full article ">
12 pages, 3788 KiB  
Article
Programmable µChopper Device with On-Chip Droplet Mergers for Continuous Assay Calibration
by Nan Shi and Christopher J. Easley
Micromachines 2020, 11(6), 620; https://doi.org/10.3390/mi11060620 - 25 Jun 2020
Cited by 11 | Viewed by 4034
Abstract
While droplet-based microfluidics is a powerful technique with transformative applications, most devices are passively operated and thus have limited real-time control over droplet contents. In this report, an automated droplet-based microfluidic device with pneumatic pumps and salt water electrodes was developed to generate [...] Read more.
While droplet-based microfluidics is a powerful technique with transformative applications, most devices are passively operated and thus have limited real-time control over droplet contents. In this report, an automated droplet-based microfluidic device with pneumatic pumps and salt water electrodes was developed to generate and coalesce up to six aqueous-in-oil droplets (2.77 nL each). Custom control software combined six droplets drawn from any of four inlet reservoirs. Using our μChopper method for lock-in fluorescence detection, we first accomplished continuous linear calibration and quantified an unknown sample. Analyte-independent signal drifts and even an abrupt decrease in excitation light intensity were corrected in real-time. The system was then validated with homogeneous insulin immunoassays that showed a nonlinear response. On-chip droplet merging with antibody-oligonucleotide (Ab-oligo) probes, insulin standards, and buffer permitted the real-time calibration and correction of large signal drifts. Full calibrations (LODconc = 2 ng mL−1 = 300 pM; LODamt = 5 amol) required <1 min with merely 13.85 nL of Ab-oligo reagents, giving cost-savings 160-fold over the standard well-plate format while also automating the workflow. This proof-of-concept device—effectively a microfluidic digital-to-analog converter—is readily scalable to more droplets, and it is well-suited for the real-time automation of bioassays that call for expensive reagents. Full article
(This article belongs to the Special Issue Droplet Microfluidics)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Microdevice design and operation. (<b>A</b>) Inlet aqueous reservoirs (1–4, colored) and one oil reservoir (black) were sampled by computer-controlled pumps based on pneumatic valves (light gray). Merging electrodes (dark blue) facilitated droplet coalescence in the widened merging region (orange), merged droplets were mixed in a zig-zag channel, and then assays were incubated in a long delay channel (orange) if needed prior to optical detection. (<b>B</b>) In this example, five ratios of standard mimics (dark) and buffer (transparent) were programmed on demand, then merged downstream. Images show the droplet groups prior to merging (see <a href="#app1-micromachines-11-00620" class="html-app">Videos S1 and S2</a>).</p> Full article ">Figure 2
<p>Continuous calibration with automated droplet formation and merging. (<b>A</b>) Raw fluorescence emission data shows that the droplet contents were programmable. Data is shown under initial settings at a higher excitation light intensity (blue) and with final settings after decreasing the light (green) in real time. (<b>B</b>) A magnified segment of this data, with pulses labeled using final, post-merge concentrations of fluorescein standard. Data from the unknown droplet is shaded in gold. (<b>C</b>) Magnified view of the oil signal shows a typical optical system drift that can be corrected using our µChopper method [<a href="#B8-micromachines-11-00620" class="html-bibr">8</a>,<a href="#B12-micromachines-11-00620" class="html-bibr">12</a>,<a href="#B22-micromachines-11-00620" class="html-bibr">22</a>]. (<b>D</b>) Histogram analysis reveals the method’s capability for a highly precise control of the droplet contents. The peaks are labeled with the pre-merge, programmed numbers of standard and buffer droplets. The inset shows the linear calibrations under the initial and final settings.</p> Full article ">Figure 3
<p>Data reshaping allowed for a unique visual inspection of the system, enabled by a precise droplet control with valves. (<b>A</b>) The raw data vector over time was reshaped into an image array using custom a MATLAB code, and image re-slicing permitted temporal tracking of each type of droplet (above) or original data recovery (right). (<b>B</b>) The system responded to the light intensity decrease by adjusting the calibration parameters, while the fit linearity and unknown determination were essentially unaffected.</p> Full article ">Figure 4
<p>Automated homogeneous immunoassays in nanoliter droplets. (<b>A</b>) Device was operated with three inlets to program the pre-merge ratio of Ab-oligo probe, insulin, and buffer droplets. (<b>B</b>) Fluorescence-quenching-based homogeneous immunoassay with Ab-oligo probes. The signal quenching is proportional to the analyte concentration with a nonlinear response curve. (<b>C</b>) Raw emission data from the automated continuous calibration. The upper inset is a zoomed view of the detector drift, and the lower inset shows that the magnitude of the drift is similar to the overall assay response. (<b>D</b>) Lock-in detection with the µChopper method allows for a reliable correction and calibration. The signal change is shown versus [insulin] (left) and log<sub>10</sub>[insulin] (right). LOD<sub>conc</sub> = 2 ng mL<sup>−1</sup> = 300 pM, while LOD<sub>amt</sub> = 5 amol. (<b>E</b>) The continuous linear calibration parameters versus log<sub>10</sub>[insulin] show the slope and y-intercept to be responsive to significant detector drifts. (<b>F</b>) The intensity histograms show that the assay responses over the 10–50 ng mL<sup>−1</sup> insulin range were closely clustered, and drift could also be observed. The calibration standards followed the drift, giving reliable calibrations over time as in part (<b>D</b>,<b>E</b>).</p> Full article ">
14 pages, 2842 KiB  
Article
Mechanically Robust, Softening Shape Memory Polymer Probes for Intracortical Recording
by Allison M. Stiller, Joshua O. Usoro, Jennifer Lawson, Betsiti Araya, María Alejandra González-González, Vindhya R. Danda, Walter E. Voit, Bryan J. Black and Joseph J. Pancrazio
Micromachines 2020, 11(6), 619; https://doi.org/10.3390/mi11060619 - 25 Jun 2020
Cited by 25 | Viewed by 3849
Abstract
While intracortical microelectrode arrays (MEAs) may be useful in a variety of basic and clinical scenarios, their implementation is hindered by a variety of factors, many of which are related to the stiff material composition of the device. MEAs are often fabricated from [...] Read more.
While intracortical microelectrode arrays (MEAs) may be useful in a variety of basic and clinical scenarios, their implementation is hindered by a variety of factors, many of which are related to the stiff material composition of the device. MEAs are often fabricated from high modulus materials such as silicon, leaving devices vulnerable to brittle fracture and thus complicating device fabrication and handling. For this reason, polymer-based devices are being heavily investigated; however, their implementation is often difficult due to mechanical instability that requires insertion aids during implantation. In this study, we design and fabricate intracortical MEAs from a shape memory polymer (SMP) substrate that remains stiff at room temperature but softens to 20 MPa after implantation, therefore allowing the device to be implanted without aids. We demonstrate chronic recordings and electrochemical measurements for 16 weeks in rat cortex and show that the devices are robust to physical deformation, therefore making them advantageous for surgical implementation. Full article
(This article belongs to the Special Issue Microelectrode Arrays and Application to Medical Devices)
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<p>SMP and silicon device design. (<b>a</b>) Optical image of a packaged SMP device with the red inset depicting 16 electrode sites on an SMP device (the electrodes appear to be black due to the SIROF coating). The Omnetics connector is sealed off with epoxy (grey encapsulation material). (<b>b</b>) Representative cross-sectional view of a gold trace and coaxial Parylene C insulation in both device variations. (<b>c</b>) A size-matched non-functional silicon device mounted in a zero insertion force (ZIF) connector.</p> Full article ">Figure 2
<p>Device implantation. (<b>a</b>) Schematic depicting bilateral implant locations (red crosses) in rat brain. The circled plus signs indicate placement of stainless steel screws. (<b>b</b>) SMP shank held over a craniotomy with resected dura immediately before implantation. Scale bar = 1 mm.</p> Full article ">Figure 3
<p>Cylinder test setup. (<b>a</b>) The rat is filmed from underneath as it rears up. (<b>b</b>) The rat rears up to explore its surroundings. The yellow circle indicates a paw touch against the cylinder.</p> Full article ">Figure 4
<p>Device robustness testing setup. The device is mounted via the connector as a cantilevered beam on a stage with the entire length of the shank suspended parallel to the ground. The tip of the device is deflected downward at a speed of 1 mm/s (indicated by downward arrow) and the shank deforms accordingly (dashed line). In the case of the silicon shank, fracture occurs after a certain displacement (d). This displacement is then transiently applied in the same manner to the SMP devices.</p> Full article ">Figure 5
<p>Chronic electrophysiological recordings. (<b>a</b>) Representative filtered data from three electrodes on one device. (<b>b</b>) Representative single unit activity on one electrode. We extracted measurements for single-unit amplitude (<b>c</b>), active electrode yield (<b>d</b>), RMS noise (<b>e</b>), and signal-to-noise ratio (<b>f</b>) from filtered wideband data. Linear regression analysis showed no change in single-unit amplitude over time. There was a decrease in active electrode yield (R<sup>2</sup> = 0.03, ρ = 0.03) and RMS noise (R<sup>2</sup> = 0.09, ρ &lt; 0.01) and an increase in SNR (R<sup>2</sup> = 0.02, ρ &lt; 0.01) over time. Data are represented as mean ± SEM.</p> Full article ">Figure 6
<p>Impedance magnitude at 1 kHz over 16 weeks. Linear regression analysis shows a slight decrease in impedance over time (R<sup>2</sup> = 0.03, ρ &lt; 0.01). Data are represented as mean ± SEM.</p> Full article ">Figure 7
<p>Representative EIS results from a single SMP device before and after deformation show minimal changes in impedance magnitude at 100 Hz, 1 kHz, and 10 kHz due to device deformation. The electrodes on this device exhibited an average decrease in impedance magnitude of −0.05 ± 4.2% (mean ± SEM) at 100 Hz (n = 16, ρ = 0.84), and an average increase in impedance magnitude of 2.8 ± 2.4% at 1 kHz (n = 16, ρ = 0.46) and 7.2 ± 1.2% at 10 kHz (n = 16, ρ &lt; 0.001). The electrode layout was such that electrode 1 was located at the tip of the shank and electrode 16 was furthest up the shank.</p> Full article ">Figure 8
<p>Representative immunofluorescent images for GFAP, NeuN, CD68, and DAPI stain in a middle brain slice containing a silicon device (top row) and an SMP device (bottom row). Scale bar = 100 µm.</p> Full article ">Figure 9
<p>Percent of paw contacts as a function of device type implanted contralateral to the preferred paw (based on baseline data). SMP probe data are represented as mean ± SEM.</p> Full article ">
14 pages, 5633 KiB  
Article
Improved Enumeration of Weakly Fluorescent CD4+ T-lymphocytes by Confining Cells in a Spinning Sample Cartridge with a Helical Minichannel
by Subin Kim, Jakir Hossain Imran, Mohiuddin Khan Shourav and Jung Kyung Kim
Micromachines 2020, 11(6), 618; https://doi.org/10.3390/mi11060618 - 25 Jun 2020
Cited by 1 | Viewed by 2246
Abstract
The CD4 (cluster of differentiation 4) counting method is used to measure the number of CD4+ T-lymphocytes per microliter of blood and to evaluate the timing of the initiation of antiretroviral therapy as well as the effectiveness of treatment in patients with human [...] Read more.
The CD4 (cluster of differentiation 4) counting method is used to measure the number of CD4+ T-lymphocytes per microliter of blood and to evaluate the timing of the initiation of antiretroviral therapy as well as the effectiveness of treatment in patients with human immunodeficiency virus. We developed a three-dimensional helical minichannel-based sample cartridge in which a thread-like microgroove formed in the cylindrical surface and configured a particle-positioning and imaging system equipped with a single DC (direct current) motor that can be controlled by a smartphone application. Confinement and enrichment of CD4 cells within a sharp focal depth along the helical minichannel is accomplished by spinning the cylindrical sample cartridge at high speed before acquiring cell images and thus CD4+ cells with weak fluorescence intensity can be detected even in a channel much deeper than existing two-dimensional flat chambers without an autofocusing module. By detecting more cells in a larger sample volume, the accuracy of the CD4 cell count is improved by a factor of 5.8 with a channel of 500 μm depth and the precision is enhanced by a factor of 1.5 with a coefficient of variation of 2.6%. Full article
(This article belongs to the Special Issue Microsystems for Point-of-Care Testing)
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<p>(<b>a</b>) Two-color-fluorescence imaging configuration with a Bluetooth-controlled DC (direct current) motor system; (<b>b</b>) smartphone application for motor control with an Arduino board; (<b>c</b>) helical minichannel filled with blood sample during acquisition of fluorescent cell images for counting.</p> Full article ">Figure 2
<p>Schematic of the sample cartridge and the cross section of the helical minichannel with depths of (<b>a</b>) 100 μm and (<b>b</b>) 500 μm.</p> Full article ">Figure 3
<p>(<b>a</b>) Schematic of particle confinement in a helical minichannel after spinning the sample cartridge; (<b>b</b>) schematic of a particle moving toward the outer wall during spinning.</p> Full article ">Figure 4
<p>Plots of velocity–displacement as a function of channel depth for channel depths of (<b>a</b>) 100 μm, (<b>b</b>) 200 μm, (<b>c</b>) 300 μm, (<b>d</b>) 400 μm and (<b>e</b>) 500 μm.</p> Full article ">Figure 5
<p>Plots of time–displacement for channel depths of (<b>a</b>) 100 μm, (<b>b</b>) 200 μm, (<b>c</b>) 300 μm, (<b>d</b>) 400 μm and (<b>e</b>) 500 μm; (<b>f</b>) Time taken by particles to reach the top of the channel depending on channel depth (h = 15 μm).</p> Full article ">Figure 6
<p>Sequence of particle and CD4 (cluster of differentiation 4) cell images taken at different z-axis offsets using a 10× objective lens; (<b>a</b>) 10-µm fluorescent bead; (<b>b</b>) fluorescently-labeled CD4+ T-lymphocyte; (<b>c</b>) comparison of the signal-to-noise ratios (SNRs) of the fluorescent bead and CD4 cell.</p> Full article ">Figure 7
<p>Particle confinement in the helical minichannel with 500 μm depth for 10-μm fluorescent beads suspended in 10% glycerol before (0 s) and after (10–120 s) spinning (<b>a</b>) at 1000 rpm, (<b>b</b>) at 2000 rpm and (<b>c</b>) at 3000 rpm. (scale bar = 0.1 mm).</p> Full article ">Figure 8
<p>Particle counts depending on time at different spin speeds (1000, 2000 and 3000 rpm).</p> Full article ">Figure 9
<p>CD4 cell counts before and after spinning for different channel depths (100 and 500 µm); (<b>a</b>) before and (<b>b</b>) after spinning in a 100-µm-deep channel; (<b>c</b>) before and (<b>d</b>) after spinning in a 500-µm-deep channel; (<b>e</b>) comparison of the number of CD4 cells per µL before and after spinning in each channel with the reference value determined by manual counting using a C-Chip.</p> Full article ">Figure 10
<p>Comparison of CD4+ cell counts in diluted blood samples from human volunteers. (<b>a</b>) Helios and ADAM-II versus PIMA; (<b>b</b>) ADAM-II versus FACSCalibur.</p> Full article ">
11 pages, 2873 KiB  
Article
Highly Integrated Elastic Island-Structured Printed Circuit Board with Controlled Young’s Modulus for Stretchable Electronics
by Duho Cho, Junhyung Kim, Pyoenggeun Jeong, Wooyoung Shim, Su Yeon Lee, Youngmin Choi and Sungmook Jung
Micromachines 2020, 11(6), 617; https://doi.org/10.3390/mi11060617 - 25 Jun 2020
Cited by 2 | Viewed by 4044
Abstract
A stretchable printed circuit board (PCB), which is an essential component of next-generation electronic devices, should be highly stretchable even at high levels of integration, as well as durable under repetitive stretching and patternable. Herein, an island-structured stretchable PCB composed of materials with [...] Read more.
A stretchable printed circuit board (PCB), which is an essential component of next-generation electronic devices, should be highly stretchable even at high levels of integration, as well as durable under repetitive stretching and patternable. Herein, an island-structured stretchable PCB composed of materials with controlled Young’s modulus and viscosity by adding a reinforcing agent or controlling the degree of crosslinking is reported. Each material was fabricated with the most effective structures through a 3D printer. The PCB was able to stretch 71.3% even when highly integrated and was patterned so that various components could be mounted. When fully integrated, the stress applied to the mounted components was reduced by 99.9% even when stretched by over 70%. Consequently, a 4 × 4 array of capacitance sensors in a stretchable keypad demonstration using our PCB was shown to work, even at 50% stretching of the PCB. Full article
(This article belongs to the Special Issue Deformable Bioelectronics Based on Functional Micro/nanomaterials)
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<p>Schematic illustration of the manufacturing process for the double layer stretchable keypad.</p> Full article ">Figure 2
<p>(<b>a</b>) Optical microscopy images of the rigid section film 14.3, 33.3, and 60 wt% glass fiber (GF), (<b>b</b>) and their Young’s modulus. (<b>c</b>) Image of the printed stretchable conductive paste on the rigid section. (<b>d</b>) Resistance changes of the printed stretchable conductive paste on the soft section (<b>left</b>) and the rigid section made with 33.3 and 60 wt% GF (<b>right</b>) according to tensile strain (75%, 3 cycles).</p> Full article ">Figure 3
<p>(<b>a</b>) Viscosity of the rigid part (with 60 wt% GF) with solvent (Black) and without solvent (Red). (<b>b</b>) Image of printed rigid part through nozzle jet printing. Inset shows a magnified optical microscopy image. (<b>c</b>) Image of variously patterned rigid part through nozzle jet printing. Inset shows a magnified optical microscopy image.</p> Full article ">Figure 4
<p>(<b>a</b>) Young’s modulus of various materials for the soft section. (<b>b</b>) Young’s modulus and elongation at the break of reverse-micelle-induced (RMI) polydimethylsiloxane (PDMS), 30:1 PDMS, and Ecoflex. (<b>c</b>) The stress–strain curves of RMI PDMS during 150% stretching over 1000 cycles. (<b>d</b>) Adhesion force of the soft sections (RMI PDMS and PDMS 30:1) with the rigid section and the intermediate section.</p> Full article ">Figure 5
<p>(<b>a</b>) Dependence of elongation at the break of the island-structured printed circuit board (iPCB) with an <span class="html-italic">R</span> ratio of 50% on the Young’s modulus of <span class="html-italic">I</span> section changes by adding GF or adjusting the amount of catalyst. (<b>b</b>) Change of linewidth and line thickness according to <span class="html-italic">z</span>-axis stacking printing. (<b>c</b>) Optical microscopy image of <span class="html-italic">z</span>-axis stacking printed <span class="html-italic">I</span> section. (<b>d</b>) Dependence of elongation at the break of the iPCB with <span class="html-italic">R</span> ratios of 0, 33%, 50%, 66%, and 80% according to the presence of the <span class="html-italic">I</span> section (<b>left</b>) and dependence of elongation at the break of the iPCB with an <span class="html-italic">R</span> ratio of 80% according to the 3D structure changes (<b>right</b>).</p> Full article ">Figure 6
<p>Stretchable keypad demonstration. (<b>a</b>) Photograph of the system. 4 × 4 array of touch sensors printed on the iPCB made with rigid–intermediate–soft (RIS) materials and connected to an Arduino (<b>left</b>). Keypad configuration (<b>right top</b>) and a circuit diagram of the system (<b>right bottom</b>). (<b>b</b>) Optical image of 50% stretched stretchable keypad (<b>left</b>). Change in capacitance during touch of ‘3’, ‘6’, ‘9’, and ‘Enter’ on the keypad (<b>right</b>). (<b>c</b>) Image of a stretchable iPCB with electrical components (chip LEDs, resistors, and battery). (<b>d</b>) Current output signals from the device at 0 and 0.5 strain.</p> Full article ">Figure 6 Cont.
<p>Stretchable keypad demonstration. (<b>a</b>) Photograph of the system. 4 × 4 array of touch sensors printed on the iPCB made with rigid–intermediate–soft (RIS) materials and connected to an Arduino (<b>left</b>). Keypad configuration (<b>right top</b>) and a circuit diagram of the system (<b>right bottom</b>). (<b>b</b>) Optical image of 50% stretched stretchable keypad (<b>left</b>). Change in capacitance during touch of ‘3’, ‘6’, ‘9’, and ‘Enter’ on the keypad (<b>right</b>). (<b>c</b>) Image of a stretchable iPCB with electrical components (chip LEDs, resistors, and battery). (<b>d</b>) Current output signals from the device at 0 and 0.5 strain.</p> Full article ">
14 pages, 4807 KiB  
Article
Wetting Properties of Transparent Anatase/Rutile Mixed Phase Glancing Angle Magnetron Sputtered Nano-TiO2 Films
by Vasiliki Vrakatseli, Ergina Farsari and Dimitrios Mataras
Micromachines 2020, 11(6), 616; https://doi.org/10.3390/mi11060616 - 25 Jun 2020
Cited by 17 | Viewed by 3514
Abstract
Transparent polycrystalline TiO2 thin films have been deposited on unheated glass substrates using RF reactive magnetron sputtering. Depositions were carried out at different glancing angles and with different total gas mixture pressures. The variation of these parameters affected the crystal phase composition [...] Read more.
Transparent polycrystalline TiO2 thin films have been deposited on unheated glass substrates using RF reactive magnetron sputtering. Depositions were carried out at different glancing angles and with different total gas mixture pressures. The variation of these parameters affected the crystal phase composition and the surface morphology. Depending on the glancing angle and the pressure, rutile, mixed anatase/ rutile and pure anatase were deposited at low substrate temperature. Both hydrophilic and hydrophobic TiO2 were obtained, exhibiting fast photoconversion to superhydrophilic upon UV irradiation. The effect of the materials physicochemical properties on the wettability and rate of the UV induced superhydrophilicity is evaluated. Full article
(This article belongs to the Special Issue Micro/Nano-surfaces: Fabrication and Applications)
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<p>Substrate geometry with respect to target surface for glancing angle depositions.</p> Full article ">Figure 2
<p>Raman spectra of the TiO<sub>2</sub> films deposited at different glancing angles and sputtering conditions.</p> Full article ">Figure 3
<p>UV-visible optical transmission spectra of the TiO<sub>2</sub> films on glass substrate.</p> Full article ">Figure 4
<p>Tauc plots for the estimation of (<b>a</b>) indirect band gap and (<b>b</b>) direct band gap of the TiO<sub>2</sub> films.</p> Full article ">Figure 5
<p>Measured apparent contact angles 10 days after the deposition and after prolonged storage in dark when the surface is stabilized versus (<b>a</b>) the glancing angle of the substrate (P<sub>t</sub> =2.4 mTorr, O<sub>2</sub> content:50%) and (<b>b</b>) the working pressure (glancing angle 75°, O<sub>2</sub> content: 32%).</p> Full article ">Figure 6
<p>Apparent water contact angles of the GLAD TiO<sub>2</sub> films, 10 days after the deposition and &gt;30 days after deposition (stabilized), along with the respective RMS surface roughness (in nm), as a function of the TiO<sub>2</sub> phase composition.</p> Full article ">Figure 7
<p>The cosine of the apparent contact angle of glancing angle deposited TiO<sub>2</sub> films (<b>a</b>) rich in rutile (65–100%) and (<b>b</b>) rich in anatase (45–100%), as a function of the RMS roughness of the surface.</p> Full article ">Figure 8
<p>3D views of the AFM images (5 μm × 5 μm) and line height profiles acquired for two hydrophobic and two hydrophilic TiO<sub>2</sub> thins films. (<b>A</b>,<b>C</b>): G60 and G75A (hydrophobic rutile), (<b>B</b>,<b>D</b>): G87 and G75B (hydrophilic anatase)</p> Full article ">Figure 9
<p>(<b>a</b>) Contact angle variation as a function of the elapsed time of exposure of the TiO<sub>2</sub> films under UV radiation (8 mW/cm<sup>2</sup>) and (<b>b</b>) contact angle relaxation during storage of the films in dark ambient conditions after the UV exposure. (<b>c</b>,<b>d</b>) Required time of UV illumination in order the TiO<sub>2</sub> films to achieve complete wetting and corresponding surface roughness versus the content in anatase. Note: separate graphs of the initially hydrophobic rutile rich TiO<sub>2</sub> and the initially hydrophilic anatase rich TiO<sub>2</sub> are plotted due to the difference in the extent of the superhydrophilic photoconversion. (<b>c</b>,<b>d</b>) are not comparable.</p> Full article ">
15 pages, 7901 KiB  
Article
The Mechanical and Physical Properties of 3D-Printed Materials Composed of ABS-ZnO Nanocomposites and ABS-ZnO Microcomposites
by Nectarios Vidakis, Markos Petousis, Athena Maniadi, Emmanuel Koudoumas, George Kenanakis, Cosmin Romanitan, Oana Tutunaru, Mirela Suchea and John Kechagias
Micromachines 2020, 11(6), 615; https://doi.org/10.3390/mi11060615 - 25 Jun 2020
Cited by 53 | Viewed by 4458
Abstract
In order to expand the mechanical and physical capabilities of 3D-printed structures fabricated via commercially available 3D printers, nanocomposite and microcomposite filaments were produced via melt extrusion, 3D-printed and evaluated. The scope of this work is to fabricate physically and mechanically improved nanocomposites [...] Read more.
In order to expand the mechanical and physical capabilities of 3D-printed structures fabricated via commercially available 3D printers, nanocomposite and microcomposite filaments were produced via melt extrusion, 3D-printed and evaluated. The scope of this work is to fabricate physically and mechanically improved nanocomposites or microcomposites for direct commercial or industrial implementation while enriching the existing literature with the methodology applied. Zinc Oxide nanoparticles (ZnO nano) and Zinc Oxide micro-sized particles (ZnO micro) were dispersed, in various concentrations, in Acrylonitrile Butadiene Styrene (ABS) matrices and printable filament of ~1.75mm was extruded. The composite filaments were employed in a commercial 3D printer for tensile and flexion specimens’ production, according to international standards. Results showed a 14% increase in the tensile strength at 5% wt. concentration in both nanocomposite and microcomposite materials, when compared to pure ABS specimens. Furthermore, a 15.3% increase in the flexural strength was found in 0.5% wt. for ABS/ZnO nano, while an increase of 17% was found on 5% wt. ABS/ZnO micro. Comparing the two composites, it was found that the ABS/ZnO microcomposite structures had higher overall mechanical strength over ABS/ZnO nanostructures. Full article
(This article belongs to the Special Issue Advanced Manufacturing Technology)
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<p>Nano- and micro-composite filaments’ and specimens’ fabrication methodology.</p> Full article ">Figure 2
<p>(<b>a</b>) X-ray diffraction (XRD) spectra of ABS/ZnO nanocomposites and (<b>b</b>) XRD spectra of ABS/ZnO micro-composites in concentrations studied.</p> Full article ">Figure 3
<p>(<b>a</b>) Scanning electron microscopy (SEM) images of pure ABS surface area; (<b>b</b>) pure ABS section area; (<b>c</b>) ABS/ZnO nano 2.5% wt. surface area; (<b>d</b>) ABS/ZnO nano 2.5% wt. section area; (<b>e</b>) ABS/ZnO nano 20% wt. surface area; (<b>f</b>) ABS/ZnO nano 20% wt. section area. “Surface area” corresponds to the 3D-printed material surface, while “section area” corresponds to the surface resulted from tensile testing.</p> Full article ">Figure 4
<p>(<b>a</b>) SEM images of pure ABS surface area; (<b>b</b>) pure ABS section area; (<b>c</b>) ABS/ZnO micro 2.5% wt. surface area; (<b>d</b>) ABS/ZnO micro 2.5% wt. section area; (<b>e</b>) ABS/ZnO micro 20% wt. surface area; (<b>f</b>) ABS/ZnO micro 20% wt. section area “Surface area” corresponds to the 3D-printed material surface, while “section area” corresponds to the surface resulted from tensile testing.</p> Full article ">Figure 5
<p>Thermogravimetric analysis (TGA) mass loss versus temperature curve for the ABS Terluran Hi-10 experimentally determined in this work and ABS polymer matrix manufacturer properties (courtesy of Ineos Styrolousion, material datasheet).</p> Full article ">Figure 6
<p>(<b>a</b>) Differential scanning calorimetry (DSC) curves for ABS, ABS/ZnO nanocomposites and (<b>b</b>) ABS/ZnO micro-composites.</p> Full article ">Figure 7
<p>(<b>a</b>) Tensile stress vs. strain graphs for ABS/ZnO nano and (<b>b</b>) ABS/ZnO micro.</p> Full article ">Figure 8
<p>(<b>a</b>) Comparative tensile strength graph and (<b>b</b>) tensile mod. of elasticity for all the materials studied (numbers in the graph points indicate the calculated deviation for each value).</p> Full article ">Figure 9
<p>(<b>a</b>) Flexure stress vs. strain graphs for (<b>b</b>) ABS/ZnO nano and ABS/ZnO micro.</p> Full article ">Figure 10
<p>(<b>a</b>) Comparative flexural strength graph and (<b>b</b>) flexural mod. of elasticity for all the materials studied (numbers in the graph points indicate the calculated deviation for each value).</p> Full article ">Figure 11
<p>Micro-Hardness Vickers results of ABS/ZnO nanocomposites (<b>a</b>) and micro-composites (<b>b</b>) versus the filler concentration (numbers in the graph points indicate the calculated deviation for each value).</p> Full article ">Figure 12
<p>Overall comparative graphs for (<b>a</b>) ABS/ZnO nanocomposites and (<b>b</b>) ABS/ZnO micro-composites, in all scenarios studied.</p> Full article ">
17 pages, 10902 KiB  
Article
Experimental Validation of Injection Molding Simulations of 3D Microparts and Microstructured Components Using Virtual Design of Experiments and Multi-Scale Modeling
by Dario Loaldi, Francesco Regi, Federico Baruffi, Matteo Calaon, Danilo Quagliotti, Yang Zhang and Guido Tosello
Micromachines 2020, 11(6), 614; https://doi.org/10.3390/mi11060614 - 24 Jun 2020
Cited by 27 | Viewed by 4479
Abstract
The increasing demand for micro-injection molding process technology and the corresponding micro-molded products have materialized in the need for models and simulation capabilities for the establishment of a digital twin of the manufacturing process. The opportunities enabled by the correct process simulation include [...] Read more.
The increasing demand for micro-injection molding process technology and the corresponding micro-molded products have materialized in the need for models and simulation capabilities for the establishment of a digital twin of the manufacturing process. The opportunities enabled by the correct process simulation include the possibility of forecasting the part quality and finding optimal process conditions for a given product. The present work displays further use of micro-injection molding process simulation for the prediction of feature dimensions and its optimization and microfeature replication behavior due to geometrical boundary effects. The current work focused on the micro-injection molding of three-dimensional microparts and of single components featuring microstructures. First, two virtual a studies were performed to predict the outer diameter of a micro-ring within an accuracy of 10 µm and the flash formation on a micro-component with mass a 0.1 mg. In the second part of the study, the influence of microstructure orientation on the filling time of a microcavity design section was investigated for a component featuring micro grooves with a 15 µm nominal height. Multiscale meshing was employed to model the replication of microfeatures in a range of 17–346 µm in a Fresnel lens product, allowing the prediction of the replication behavior of a microfeature at 91% accuracy. The simulations were performed using 3D modeling and generalized Navier–Stokes equations using a single multi-scale simulation approach. The current work shows the current potential and limitations in the use of micro-injection molding process simulations for the optimization of micro 3D-part and microstructured components. Full article
(This article belongs to the Special Issue Latest Advancements in Micro Nano Molding Technologies – Process Developments and Optimization, Materials, Applications, Key Enabling Technologies)
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<p>Comparison of µIM modeling cases for parts featuring micro/nano surface structures based on the structures’ aspect ratio, height, and feature geometry [<a href="#B9-micromachines-11-00614" class="html-bibr">9</a>,<a href="#B10-micromachines-11-00614" class="html-bibr">10</a>,<a href="#B11-micromachines-11-00614" class="html-bibr">11</a>,<a href="#B17-micromachines-11-00614" class="html-bibr">17</a>,<a href="#B18-micromachines-11-00614" class="html-bibr">18</a>,<a href="#B19-micromachines-11-00614" class="html-bibr">19</a>,<a href="#B20-micromachines-11-00614" class="html-bibr">20</a>,<a href="#B21-micromachines-11-00614" class="html-bibr">21</a>,<a href="#B22-micromachines-11-00614" class="html-bibr">22</a>,<a href="#B23-micromachines-11-00614" class="html-bibr">23</a>,<a href="#B24-micromachines-11-00614" class="html-bibr">24</a>,<a href="#B25-micromachines-11-00614" class="html-bibr">25</a>,<a href="#B26-micromachines-11-00614" class="html-bibr">26</a>,<a href="#B27-micromachines-11-00614" class="html-bibr">27</a>,<a href="#B28-micromachines-11-00614" class="html-bibr">28</a>,<a href="#B29-micromachines-11-00614" class="html-bibr">29</a>].</p> Full article ">Figure 2
<p>Design specification of the polymer micro-ring (<b>left</b>) and micro-molded parts (<b>right</b>) [<a href="#B30-micromachines-11-00614" class="html-bibr">30</a>].</p> Full article ">Figure 3
<p>Design specifications of the polymer micro-cap in the analysis (<b>left</b> and <b>center</b>); scanning electron microscope image of the micro-injection molded part (<b>right</b>) [<a href="#B31-micromachines-11-00614" class="html-bibr">31</a>].</p> Full article ">Figure 4
<p>Multi-scale mesh of Case 1 including: sprue, runners, and multicavity tooling system (<b>left</b>); detailed view of the molded part and of the venting structure (<b>right</b>) [<a href="#B31-micromachines-11-00614" class="html-bibr">31</a>].</p> Full article ">Figure 5
<p>Multi-scale mesh and modified model geometry of Case 2 to include the flash formation in the simulation of the micro-cap [<a href="#B31-micromachines-11-00614" class="html-bibr">31</a>].</p> Full article ">Figure 6
<p>Design specification of the demonstrator with light selective reflection surface structures.</p> Full article ">Figure 7
<p>Main effects plot of the process factors on the outer diameter of the micro-ring [<a href="#B31-micromachines-11-00614" class="html-bibr">31</a>].</p> Full article ">Figure 8
<p>Simulated optimal process conditions for the outer diameter of the micro-ring.</p> Full article ">Figure 9
<p>(<b>a</b>) Simulated flash formation during cavity filling; (<b>b</b>) real flash on the part; and (<b>c</b>) simulated flash (the dimensional scale bar is equal in both images) [<a href="#B31-micromachines-11-00614" class="html-bibr">31</a>].</p> Full article ">Figure 10
<p>Main effects plot of the flash area for the experiments A<sub>flash-meas</sub> (in black) and simulations A<sub>flash-sim</sub> (in red). Note that the scales for the two sets of results are different, but the ranges shown are equal. Interval bars represent the standard errors of experimental data [<a href="#B31-micromachines-11-00614" class="html-bibr">31</a>].</p> Full article ">Figure 11
<p>Design specification of the micro-optical reflector (<b>left</b>) with a highlight of its surface structures (<b>center</b>); injection molded part and tool cavity insert (<b>right</b>) [<a href="#B32-micromachines-11-00614" class="html-bibr">32</a>].</p> Full article ">Figure 12
<p>Design specification of the analyzed Fresnel lens (<b>left</b>) and detail of the low aspect ratio surface structures (<b>center</b>); injection molded parts (<b>right</b>) [<a href="#B33-micromachines-11-00614" class="html-bibr">33</a>].</p> Full article ">Figure 13
<p>The multi-scale mesh of the optical demonstrator with selected surface features included in the geometry [<a href="#B35-micromachines-11-00614" class="html-bibr">35</a>].</p> Full article ">Figure 14
<p>The multi-scale mesh of the Fresnel lens with partial surface mesh refinement at (<b>a</b>) part level, (<b>b</b>) structured area level, and (<b>c</b>) at single micro feature level.</p> Full article ">Figure 15
<p>Injection speed profiles sampled from the machine controller for Cases 3 (<b>a</b>) and 4 (<b>b</b>).</p> Full article ">Figure 16
<p>Injection pressure at the injection location comparison from the simulation and actual value for Cases 3 (<b>a</b>) and 4 (<b>b</b>).</p> Full article ">Figure 17
<p>Filling time comparison from the microfeature and bottom polished surface as a function of the flow length for the right (<b>a</b>), left (<b>b</b>), and central (<b>c</b>) section of Case 3 with the summary difference of filling time for each condition (<b>d</b>).</p> Full article ">Figure 18
<p>Filling volume comparison from the actual and simulated values for a short shot at meso- (<b>a</b>) and microscale (<b>c</b>), and full replication for the meso- (<b>b</b>) and microscale (<b>d</b>).</p> Full article ">
13 pages, 1515 KiB  
Article
Design Applicable 3D Microfluidic Functional Units Using 2D Topology Optimization with Length Scale Constraints
by Yuchen Guo, Hui Pan, Eddie Wadbro and Zhenyu Liu
Micromachines 2020, 11(6), 613; https://doi.org/10.3390/mi11060613 - 24 Jun 2020
Cited by 6 | Viewed by 3963
Abstract
Due to the limits of computational time and computer memory, topology optimization problems involving fluidic flow frequently use simplified 2D models. Extruded versions of the 2D optimized results typically comprise the 3D designs to be fabricated. In practice, the depth of the fabricated [...] Read more.
Due to the limits of computational time and computer memory, topology optimization problems involving fluidic flow frequently use simplified 2D models. Extruded versions of the 2D optimized results typically comprise the 3D designs to be fabricated. In practice, the depth of the fabricated flow channels is finite; the limited flow depth together with the no-slip condition potentially make the fluidic performance of the 3D model very different from that of the simplified 2D model. This discrepancy significantly limits the usefulness of performing topology optimization involving fluidic flow in 2D—at least if special care is not taken. Inspired by the electric circuit analogy method, we limit the widths of the microchannels in the 2D optimization process. To reduce the difference of fluidic performance between the 2D model and its 3D counterpart, we propose an applicable 2D optimization model, and ensure the manufacturability of the obtained layout, combinations of several morphology-mimicking filters impose maximum or minimum length scales on the solid phase or the fluidic phase. Two typical Lab-on-chip functional units, Tesla valve and fluidic channel splitter, are used to illustrate the validity of the proposed application of length scale control. Full article
(This article belongs to the Special Issue Optimization of Microfluidic Devices)
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<p>The hydraulic resistance changes with the length (red), height (blue), and width (green) of the channel, <math display="inline"><semantics> <mrow> <mi>η</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.</p> Full article ">Figure 2
<p>The four basic morphological operators defined by the ball <span class="html-italic">B</span> acting on the set <span class="html-italic">S</span>.</p> Full article ">Figure 3
<p>The computational domain <math display="inline"><semantics> <mo>Ω</mo> </semantics></math> for the Tesla valve.</p> Full article ">Figure 4
<p>Two optimized Tesla valves with the value of <math display="inline"><semantics> <msub> <mi>C</mi> <mi>max</mi> </msub> </semantics></math> is 0.351 (<b>a</b>) and 0.551 (<b>b</b>), respectively.</p> Full article ">Figure 5
<p>Tesla valve optimized with the full length scale control optimization Formulation (<a href="#FD15-micromachines-11-00613" class="html-disp-formula">15</a>).</p> Full article ">Figure 6
<p>Reverse flow velocity field of the 2D model (<b>a</b>) and its 3D counterpart (<b>b</b>) for the optimized Tesla valve with the value of <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mi>max</mi> </msub> <mo>=</mo> <mn>0.408</mn> </mrow> </semantics></math> in <a href="#micromachines-11-00613-f004" class="html-fig">Figure 4</a>.</p> Full article ">Figure 7
<p>Reverse flow velocity field of the 2D model (<b>a</b>) and its 3D counterpart (<b>b</b>) for the optimized Tesla valve with the value of <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mi>max</mi> </msub> <mo>=</mo> <mn>0.600</mn> </mrow> </semantics></math> in <a href="#micromachines-11-00613-f004" class="html-fig">Figure 4</a>.</p> Full article ">Figure 8
<p>Reverse flow velocity field of the 2D model (<b>a</b>) and its 3D counterpart (<b>b</b>) for the optimized Tesla valve in <a href="#micromachines-11-00613-f005" class="html-fig">Figure 5</a>.</p> Full article ">Figure 9
<p>The difference <math display="inline"><semantics> <msub> <mi>δ</mi> <mn>1</mn> </msub> </semantics></math> of three optimization results between 2D and 3D models with the ratio of depth to width of the inlet <span class="html-italic">n</span>.</p> Full article ">Figure 10
<p>Computational domain for the second test problem. Here, the computational domain <math display="inline"><semantics> <mo>Ω</mo> </semantics></math> comprises the design domain <math display="inline"><semantics> <msub> <mo>Ω</mo> <mi>D</mi> </msub> </semantics></math> as well as four channels <math display="inline"><semantics> <msub> <mo>Ω</mo> <mi>C</mi> </msub> </semantics></math> that are connected to the inlet and outlets of the domain.</p> Full article ">Figure 11
<p>Optimized designs with aim to obtain equivalent outlet flowrate.</p> Full article ">Figure 12
<p>The difference <math display="inline"><semantics> <msub> <mi>δ</mi> <mn>2</mn> </msub> </semantics></math> of four optimization results between 2D and 3D models with the ratio of depth to width of the inlet <span class="html-italic">n</span>.</p> Full article ">
33 pages, 2680 KiB  
Review
Tissue-Engineered Models for Glaucoma Research
by Renhao Lu, Paul A. Soden and Esak Lee
Micromachines 2020, 11(6), 612; https://doi.org/10.3390/mi11060612 - 24 Jun 2020
Cited by 12 | Viewed by 6180
Abstract
Glaucoma is a group of optic neuropathies characterized by the progressive degeneration of retinal ganglion cells (RGCs). Patients with glaucoma generally experience elevations in intraocular pressure (IOP), followed by RGC death, peripheral vision loss and eventually blindness. However, despite the substantial economic and [...] Read more.
Glaucoma is a group of optic neuropathies characterized by the progressive degeneration of retinal ganglion cells (RGCs). Patients with glaucoma generally experience elevations in intraocular pressure (IOP), followed by RGC death, peripheral vision loss and eventually blindness. However, despite the substantial economic and health-related impact of glaucoma-related morbidity worldwide, the surgical and pharmacological management of glaucoma is still limited to maintaining IOP within a normal range. This is in large part because the underlying molecular and biophysical mechanisms by which glaucomatous changes occur are still unclear. In the present review article, we describe current tissue-engineered models of the intraocular space that aim to advance the state of glaucoma research. Specifically, we critically evaluate and compare both 2D and 3D-culture models of the trabecular meshwork and nerve fiber layer, both of which are key players in glaucoma pathophysiology. Finally, we point out the need for novel organ-on-a-chip models of glaucoma that functionally integrate currently available 3D models of the retina and the trabecular outflow pathway. Full article
(This article belongs to the Special Issue Mechanobiology and Biologically Inspired Engineering)
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<p>Physiology structure of the eye.</p> Full article ">Figure 2
<p>Substructures of trabecular meshwork and Schlemm’s canal.</p> Full article ">Figure 3
<p>Physiological and pathologic structure of optic nerve head region. NFL: nerve fiber layer, RGCL: retina ganglion cell layer, IPL: inner plexiform layer, INL: inner nuclear layer, OPL: outer plexiform layer, ONL: outer nuclear layer, IS/OS: inner segment/outer segment, RPE: retina pigmented epithelium.</p> Full article ">Figure 4
<p>2D and 3D models of trabecular meshwork and Schlemm’s canal. (<b>A</b>) Comparison of TM cells on planar surface (<b>a</b>) and groove-patterned nano-surface (<b>b</b>,<b>c</b>). The actin filaments (green) were randomly oriented on planar surface but aligned on patterned surface. Blue: nuclei [<a href="#B112-micromachines-11-00612" class="html-bibr">112</a>]; (<b>B</b>) TM and SC models based on porous SU-8 scaffolds; (<b>i</b>) fabrication of SU-8 scaffolds; (<b>a</b>) pre-cleaned silica wafer treated with a sacrificial layer; (<b>b</b>) photoresist SU-8 2010 coating; (<b>c</b>) UV-exposure using chrome mask; (<b>d</b>) post-exposure bake; (<b>e</b>) development to produce SU-8 freestanding scaffold; (<b>f</b>) HTM cell seeding on the SU-8 scaffold followed by 3D-culture; (<b>g</b>) steroid-treatment to generate glaucomatous 3D HTM model [<a href="#B114-micromachines-11-00612" class="html-bibr">114</a>]; (<b>ii</b>) comparison of human Schlemm’s canal endothelial cells on glass coverslip and SU-8 porous scaffold. F-actin staining showed better fiber alignment on SU-8 scaffold. Expression cell characteristic marker CD31, which is lost in 2D-culture, was also recovered on SU-8 scaffold. Other characteristic markers—VE-cadherin and fibulin-2—were maintained. Scale bar is 100 μm [<a href="#B92-micromachines-11-00612" class="html-bibr">92</a>]; (<b>C</b>) human Schlemm’s canal endothelial cells were cultured on Transwell; (<b>i</b>) diagram of the perfusion system; (<b>ii</b>) giant vacuole-like structures (arrows) observed with perfusion [<a href="#B115-micromachines-11-00612" class="html-bibr">115</a>]; (<b>D</b>) (<b>i</b>) combining TM cells with Max8B hydrogel to reconstruct 3D environment; (<b>ii</b>) 3D-reconstruction of TM cells in MAX8B scaffold; green: F-actin; blue: nuclei red [<a href="#B116-micromachines-11-00612" class="html-bibr">116</a>]. Figure republished with permission from each indicated reference ([<a href="#B112-micromachines-11-00612" class="html-bibr">112</a>] for part A, [<a href="#B92-micromachines-11-00612" class="html-bibr">92</a>,<a href="#B114-micromachines-11-00612" class="html-bibr">114</a>] for part B, [<a href="#B115-micromachines-11-00612" class="html-bibr">115</a>] for part C, [<a href="#B116-micromachines-11-00612" class="html-bibr">116</a>] for part D).</p> Full article ">Figure 5
<p>2D models of retina ganglion cell. (<b>A</b>) RGCs cultured on radial electrospun scaffolds mimic the axonal orientation of retina. Production and optimization of the radial electrospun scaffold. (<b>a</b>) Diagram of a 1.8-cm diameter radial collector containing a conducting central pole and rim grounded to the same source; (<b>b</b>) top view of an electrospun radial scaffold; (<b>c</b>,<b>d</b>) SEM image of peripheral radial fiber zone (<b>c</b>) and central random fiber zone (<b>d</b>); (<b>e</b>) fluorescence image of RGCs on radial scaffolds prohibited 81.1% ± 2.8 alignment of neurites in radial orientation. Green: β3-tubulin; (<b>f</b>) orientation analysis of RGC neurites on different scaffolds. No significant difference was observed between retinal explants and radial scaffold. Scale bars: b: 5 mm, c: 50 μm, d: 100 μm, e: 1 mm [<a href="#B147-micromachines-11-00612" class="html-bibr">147</a>]; (<b>B</b>) thermal-inkjet 3D cell printing techniques can mimic the in vivo RGC distribution on retina. (<b>a</b>) estimated RGC distribution on retina, including higher cell density near the optic nerve head and lower density at the fovea (*); (<b>b</b>) RGC distribution results by inkjet 3D printing; scale bar: 550 μm [<a href="#B148-micromachines-11-00612" class="html-bibr">148</a>]; (<b>C</b>) apparatus applying adjustable hydrostatic pressure to primary RGCs based on Pascal’s law. (<b>a</b>) diagram of the apparatus, a transparent reservoir connecting with multiple PDMS chambers, which are containing primary RGC cultures; (<b>b</b>,<b>c</b>) representative fluorescence images of primary RGCs cultured inside a PDMS chamber at day 3 in vitro. RGCs were positively stained with TUJ1 (green) and BRN3A (Red), which are neuronal-specific and RGC-specific, respectively [<a href="#B149-micromachines-11-00612" class="html-bibr">149</a>]. Figure republished with permission from each indicated reference ([<a href="#B147-micromachines-11-00612" class="html-bibr">147</a>] for part A, [<a href="#B148-micromachines-11-00612" class="html-bibr">148</a>] for part B, [<a href="#B149-micromachines-11-00612" class="html-bibr">149</a>] for part C).</p> Full article ">Figure 6
<p>3D models of retina ganglion cell. (<b>A</b>): (<b>a</b>): Schematic showing the hydrogel preparation procedures and experimental plan for cell seeding and analysis for the tunable hydrogel. RGCs; (<b>b</b>) and amacrine cells; (<b>c</b>) cultured in tunable hydrogels composed of poly(ethylene glycol) and poly(l-lysine); (<b>d</b>) showed both cell types under lower magnification. Both RGCs and amacrine cells migrated into hydrogels and extended neurites in three dimensions. Cells were stained using calcein-AM (green). Scale bar: i, ii: 50 μm, iii: 200 μm [<a href="#B153-micromachines-11-00612" class="html-bibr">153</a>]; (<b>B</b>) injectable hydrogel for RGC regeneration. The mix of RGCs and polymer is at solution state at room temperature. After injected, it would become hydrogel at 37 °C and fix on retina. SEM showed a laminar sheet-like structure of the hydrogel [<a href="#B154-micromachines-11-00612" class="html-bibr">154</a>]. Figure republished with permission from each indicated reference ([<a href="#B153-micromachines-11-00612" class="html-bibr">153</a>] for part A, [<a href="#B154-micromachines-11-00612" class="html-bibr">154</a>] for part B).</p> Full article ">
16 pages, 3672 KiB  
Article
Pushing the Limits of Spatial Assay Resolution for Paper-Based Microfluidics Using Low-Cost and High-Throughput Pen Plotter Approach
by Reza Amin, Fariba Ghaderinezhad, Caleb Bridge, Mikail Temirel, Scott Jones, Panteha Toloueinia and Savas Tasoglu
Micromachines 2020, 11(6), 611; https://doi.org/10.3390/mi11060611 - 24 Jun 2020
Cited by 19 | Viewed by 3789
Abstract
To transform from reactive to proactive healthcare, there is an increasing need for low-cost and portable assays to continuously perform health measurements. The paper-based analytical devices could be a potential fit for this need. To miniaturize the multiplex paper-based microfluidic analytical devices and [...] Read more.
To transform from reactive to proactive healthcare, there is an increasing need for low-cost and portable assays to continuously perform health measurements. The paper-based analytical devices could be a potential fit for this need. To miniaturize the multiplex paper-based microfluidic analytical devices and minimize reagent use, a fabrication method with high resolution along with low fabrication cost should be developed. Here, we present an approach that uses a desktop pen plotter and a high-resolution technical pen for plotting high-resolution patterns to fabricate miniaturized paper-based microfluidic devices with hundreds of detection zones to conduct different assays. In order to create a functional multiplex paper-based analytical device, the hydrophobic solution is patterned on the cellulose paper and the reagents are deposited in the patterned detection zones using the technical pens. We demonstrated the effect of paper substrate thickness on the resolution of patterns by investigating the resolution of patterns on a chromatography paper with altered effective thickness. As the characteristics of the cellulose paper substrate such as thickness, resolution, and homogeneity of pore structure affect the obtained patterning resolution, we used regenerated cellulose paper to fabricate detection zones with a diameter as small as 0.8 mm. Moreover, in order to fabricate a miniaturized multiplex paper-based device, we optimized packing of the detection zones. We also showed the capability of the presented method for fabrication of 3D paper-based microfluidic devices with hundreds of detection zones for conducting colorimetric assays. Full article
(This article belongs to the Section D：Materials and Processing)
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<p>High-resolution fabrication of multiplex paper-based microfluidic devices using a pen plotter machine and high-resolution technical pens. (<b>a</b>) Desktop pen plotter with a high-resolution technical pen. (<b>b</b>) High-resolution technical pen with 0.1 mm plastic tip used for patterning hydrophobic solution to create detection zones. (<b>c</b>) Technical pen nib with 0.1 mm plastic tip used for patterning hydrophobic solution on paper substrate. (<b>d</b>,<b>e</b>) Cross-section of chromatography paper (<b>d</b>), chromatography paper after being coated with hydrophobic solution using the wide marker (<b>e</b>), regenerated paper (<b>f</b>), and corresponding circular pattern (2 mm diameter) on those paper substrates. The yellow food dye is applied to the hydrophilic side of paper to distinguish it from hydrophobic side.</p> Full article ">Figure 2
<p>Evaluation of decreasing effective paper thickness on the resolution of patterns. (<b>a</b>) The custom-designed wide marker holder connected to the pen plotter to deposit a layer of hydrophobic ink on the chromatography paper. (<b>b</b>) Graph of percentage of food dye penetration through the thickness of paper (indicating the effective hydrophilic thickness of paper) versus the plotting speed percentage used to plot hydrophobic solution on the backside of chromatography paper. (<b>c</b>) Images of chromatography paper cross-sections after being coated with hydrophobic solution using the wide marker plotted for various speeds. The yellow food dye is applied to the hydrophilic side of paper to distinguish it from the hydrophobic side of paper. (<b>d</b>) Graph of line thickness of patterns on the chromatography paper with 50%, 75%, and 100% effective thickness (<span class="html-italic">N</span> = 6 and the error bar shows the standard deviation). (<b>e</b>) Image of a circular pattern (2 mm diameter) on the chromatography paper with 50% effective thickness and grayscale intensity analysis of food dye in detection area.</p> Full article ">Figure 3
<p>Physical characterization of Whatman grade 1 and regenerated cellulose paper. (<b>a</b>) SEM image with 250× magnification and (<b>b</b>) 750× magnification of the laminated Whatman grade 1 cellulose paper, showing the 45° view of surface and cross-section. (<b>c</b>) SEM image with 250× magnification and (<b>d</b>) 750× magnification of the Whatman grade 1 cellulose paper surface. (<b>e</b>) SEM image with 500× magnification and (<b>f</b>) 1500× magnification of the laminated Whatman regenerated cellulose paper, showing the 45° view of surface and cross-section. (<b>g</b>) SEM image with 5000× magnification and (<b>h</b>) 10,000× magnification of the Whatman regenerated cellulose paper surface.</p> Full article ">Figure 4
<p>Characterization of high-resolution fabrication of detection zones and channels. (<b>a</b>) The resolution of 0.03 mm fiber technical pen on regenerated paper with optimal 3% drawing speed (<span class="html-italic">N</span> = 9 and the error bar shows the standard deviation); (<b>b</b>) the resolution of 0.05 mm fiber technical pen on regenerated paper with optimal 6% drawing speed (<span class="html-italic">N</span> = 9 and the error bar shows the standard deviation); (<b>c</b>) the resolution of 0.1 mm fiber technical pen on regenerated paper with optimal 11% drawing speed (<span class="html-italic">N</span> = 9 and the error bar shows the standard deviation). The results measured using MATLAB script at 8 angles around each reaction area across reaction areas. (<b>d</b>) The graph of the measured microfluidic flow channel width versus the plotted channel width (<span class="html-italic">N</span> = 8 and the error bar shows the standard deviation). The channels are plotted using the 0.1 fiber technical pen with 11% drawing speed and the channel widths are measured in ten equidistant locations using ImageJ software across three test repeats. (<b>e</b>) The cross-sectional image taken of each channel. The channels are filled with yellow food dye to clarify channel vs. barrier. (<b>f</b>) The average time to fill bulb for each corresponding equal channel test (<span class="html-italic">N</span> = 8 and the error bar shows the standard deviation). The color-altered images above the chart display the flow state as the first bulb was completely filled (star marks first bulb to fill).</p> Full article ">Figure 5
<p>Packing density analysis of closely patterned detection zones. (<b>a</b>,<b>b</b>) High-resolution packing of detection zones on Whatman regenerated paper (<b>a</b>) and Whatman grade 1 paper (<b>b</b>). The diameter of circles in each pattern is 2 mm. The center-to-center distance between adjacent circles starts at 2 mm in the first pattern and decreases by 0.2 mm in each pattern. (<b>c</b>) Graph of pattern size versus center-to-center distance between adjacent circles in subfigure a and b (<span class="html-italic">N</span> = 9 and the error bar shows the standard deviation). (<b>d</b>,<b>e</b>) High-resolution fabrication of detection zones on Whatman regenerated paper (<b>d</b>) and Whatman grade 1 paper (<b>e</b>). The diameter of circles and center-to-center distance in the first pattern is 2 mm and 3 mm, respectively. The diameter of circles and the center-to-center distance between adjacent circles decrease by 0.2 mm and 0.3 mm in each pattern, respectively (the diameter of circles and the center-to-center distance of pattern 6 are 1 mm and 1.5 mm, respectively). (<b>f</b>) Graph of pattern size versus diameter of circles of subfigures d and e (<span class="html-italic">N</span> = 9 and the error bar shows the standard deviation). (<b>g</b>) Graph of grayscale intensity analysis of food dye in detection zone of pattern 1–4 of subfigure a. (<b>h</b>) Graph of grayscale intensity analysis of food dye in detection zone of pattern 3–6 of subfigure d.</p> Full article ">Figure 6
<p>High-resolution and multiplex paper-based microfluidic analytical device. (<b>a</b>) Layers and fabrication steps of the high-resolution paper-based microfluidic device. (<b>b</b>) Color change of the indicators, i.e., bromothymol blue and bromocresol green, for a range of pH 4 to 10. (<b>c</b>,<b>d</b>) Calibration curves for determining pH of the solutions by two indicators, bromothymol blue (<b>c</b>) and bromocresol green (<b>d</b>) using CIExyY color space. (<b>e</b>) Images of a device with 256 detection zones after applying the pH 10 sample to the sample pad. Using the technical pen and pen plotter, the detection zones are automatically filled with bromothymol blue (R1) and methyl red (R2) pH indicators with any given arbitrary pattern. (<b>f</b>) Photograph of a device with 512 detection zones filled with bromothymol blue (R1) and methyl red (R2) pH indicators, after applying the pH 4 sample to the sample pad.</p> Full article ">
12 pages, 2137 KiB  
Article
Mechanical Rupture-Based Antibacterial and Cell-Compatible ZnO/SiO2 Nanowire Structures Formed by Bottom-Up Approaches
by Taisuke Shimada, Takao Yasui, Akihiro Yonese, Takeshi Yanagida, Noritada Kaji, Masaki Kanai, Kazuki Nagashima, Tomoji Kawai and Yoshinobu Baba
Micromachines 2020, 11(6), 610; https://doi.org/10.3390/mi11060610 - 24 Jun 2020
Cited by 19 | Viewed by 4455
Abstract
There are growing interests in mechanical rupture-based antibacterial surfaces with nanostructures that have little toxicity to cells around the surfaces; however, current surfaces are fabricated via top-down nanotechnologies, which presents difficulties to apply for bio-surfaces with hierarchal three-dimensional structures. Herein, we developed ZnO/SiO [...] Read more.
There are growing interests in mechanical rupture-based antibacterial surfaces with nanostructures that have little toxicity to cells around the surfaces; however, current surfaces are fabricated via top-down nanotechnologies, which presents difficulties to apply for bio-surfaces with hierarchal three-dimensional structures. Herein, we developed ZnO/SiO2 nanowire structures by using bottom-up approaches and demonstrated to show mechanical rupture-based antibacterial activity and compatibility with human cells. When Escherichia coli were cultured on the surface for 24 h, over 99% of the bacteria were inactivated, while more than 80% of HeLa cells that were cultured on the surface for 24 h were still alive. This is the first demonstration of mechanical rupture-based bacterial rupture via the hydrothermally synthesized nanowire structures with antibacterial activity and cell compatibility. Full article
(This article belongs to the Special Issue Advances in Nanofluidics)
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<p>(<b>a</b>) Schematic illustrations of nanostructures on the wing of <span class="html-italic">P. claripennis</span> (upper) and antibacterial nanowire substrate (lower). Although arraigned nanowire structures are simply illustrated here, fabricated nanowires were randomly orientated. (<b>b</b>) Schematic illustrations of (i) a bacterium and (ii) human cell on nanowire structures. While the human cell attached on the nanowire structures was alive, the bacterium on the structures was mechanically ruptured and inactivated. (<b>c</b>) Schematic illustrations of the bacterium rupture mechanism. (i) A cell membrane of the bacterium was attached on the nanostructure. (ii) The membrane was stretched via the nanostructure and the surface area of the membrane increased. (iii) The membrane was ruptured due to too much stretching.</p> Full article ">Figure 2
<p>(<b>a</b>) Scanning electron microscope (SEM) images of ZnO nanowire (upper) and ZnO/SiO<sub>2</sub> nanowire (lower) as a top view (scale bars, 500 nm). (<b>b</b>) Nanowire diameter of ZnO nanowires (red) and ZnO/SiO<sub>2</sub> nanowires (blue). (<b>c</b>) Elemental mapping images by field-emission scanning electron microscope (FESEM) or scanning transmission electron microscope (STEM); Zn Kα, Si Kα, O Kα, and merged. Merged images were constructed from Zn Kα (green) and Si Kα (blue). Mapping images are for: (i) free-standing ZnO nanowires (scale bars, 1 µm), (ii) free-standing ZnO/SiO<sub>2</sub> nanowires (scale bars, 1 µm) and (iii) single ZnO/SiO<sub>2</sub> nanowire (scale bars, 100 nm).</p> Full article ">Figure 3
<p>(<b>a</b>) Counting viable bacteria cultured on each substrate. (i,ii) Fluorescence images of bacteria on each substrate (i) before and (ii) after washing out (scale bars, 100 µm). (iii) Photographs of an agar medium with colonies. Bacteria collected from each substrate were cultured on an agar medium to count colonies. (<b>b</b>) Antibacterial activity value for each substrate. Antibacterial activity value was normalized by that of the bare glass substrate. (<b>c</b>) SEM images of a bacterium cultured on (i) bare glass substrate (scale bar, 1 µm) and (ii) ZnO/SiO<sub>2</sub> nanowire substrate (scale bars, 1 µm and 200 nm (insertion)).</p> Full article ">Figure 4
<p>(<b>a</b>) Fluorescence images of HeLa cells cultured on various substrates: (i) bare glass, (ii) ZnO film, (iii) ZnO nanowires, (iv) SiO<sub>2</sub>-deposited ZnO film, (v) ZnO/SiO<sub>2</sub> nanowires (upper, merged images of cells stained by calcein-acetoxymethyl (AM) and PI (propidium iodide); lower, fluorescence images of cells stained by PI; scale bars, 100 µm). (<b>b</b>) Cell viability of HeLa cells cultured on each substrate. These viabilities were measured by using flow cytometry and viability of the cells on bare glass substrate was defined as 100%. (<b>c</b>) SEM images of HeLa cells cultured on ZnO/SiO<sub>2</sub> nanowire substrate (scale bars, 5 µm (upper) and 500 nm (lower)).</p> Full article ">
13 pages, 2203 KiB  
Article
Effect of Various Defects on 4H-SiC Schottky Diode Performance and Its Relation to Epitaxial Growth Conditions
by Jinlan Li, Chenxu Meng, Le Yu, Yun Li, Feng Yan, Ping Han and Xiaoli Ji
Micromachines 2020, 11(6), 609; https://doi.org/10.3390/mi11060609 - 24 Jun 2020
Cited by 11 | Viewed by 3841
Abstract
In this paper, the chemical vapor deposition (CVD) processing for 4H-SiC epilayer is investigated with particular emphasis on the defects and the noise properties. It is experimentally found that the process parameters of C/Si ratio strongly affect the surface roughness of epilayers and [...] Read more.
In this paper, the chemical vapor deposition (CVD) processing for 4H-SiC epilayer is investigated with particular emphasis on the defects and the noise properties. It is experimentally found that the process parameters of C/Si ratio strongly affect the surface roughness of epilayers and the density of triangular defects (TDs), while no direct correlation between the C/Si ratio and the deep level defect Z1/2 could be confirmed. By adjusting the C/Si ratio, a decrease of several orders of magnitudes in the noise level for the 4H-SiC Schottky barrier diodes (SBDs) could be achieved attributing to the improved epilayer quality with low TD density and low surface roughness. The work should provide a helpful clue for further improving the device performance of both the 4H-SiC SBDs and the Schottky barrier ultraviolet photodetectors fabricated on commercial 4H-SiC wafers. Full article
(This article belongs to the Special Issue Miniaturized Silicon Photodetectors: New Perspectives and Applications)
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<p>(<b>a</b>) Room temperature micro-photoluminescence (PL) spectra. The insets show scanning electron microscopy (SEM) images of region A (non-triangular defects (TDs)) and region B (TDs); (<b>b</b>) Micro-Raman spectra corresponding to the A and B positions in the 4H-SiC epilayer grown with C/Si = 1.1. The inset is a comparison of the intensity of the Raman peak at 796 cm<sup>−1</sup> in the enlarged view.</p> Full article ">Figure 2
<p>The C/Si ratio dependence of TDs density for 4H-SiC epilayers (#1~#3).</p> Full article ">Figure 3
<p>(<b>a</b>) The dependence of the mean reverse current density on C/Si ratio for Ni/4H-SiC Schottky barrier diodes (SBDs) under V<sub>R</sub> = −200 V. The inset shows reverse <span class="html-italic">I-V</span> characteristics of a representative sample (Ni/4H-SiC SBDs with C/Si = 1); (<b>b</b>) Forward <span class="html-italic">I-V</span> characteristics of Ni/4H-SiC SBDs under different C/Si ratios (C/Si = 0.9, 1 or 1.1). The inset shows the <span class="html-italic">C</span>-<span class="html-italic">V</span> characteristics of Ni/4H-SiC SBDs; (<b>c</b>) Frequency dependence of the spectral noise density (S<sub>I</sub>) for Ni/4H-SiC SBDs with C/Si = 0.9 at room temperature under <span class="html-italic">V<sub>R</sub></span> = −10~−200 V, the inset shows the bias voltage dependence of the spectral noise density at 1K Hz; (<b>d</b>) Noise spectra of Ni/4H-SiC SBDs with C/Si ratios (C/Si = 0.9, 1 or 1.1).</p> Full article ">Figure 3 Cont.
<p>(<b>a</b>) The dependence of the mean reverse current density on C/Si ratio for Ni/4H-SiC Schottky barrier diodes (SBDs) under V<sub>R</sub> = −200 V. The inset shows reverse <span class="html-italic">I-V</span> characteristics of a representative sample (Ni/4H-SiC SBDs with C/Si = 1); (<b>b</b>) Forward <span class="html-italic">I-V</span> characteristics of Ni/4H-SiC SBDs under different C/Si ratios (C/Si = 0.9, 1 or 1.1). The inset shows the <span class="html-italic">C</span>-<span class="html-italic">V</span> characteristics of Ni/4H-SiC SBDs; (<b>c</b>) Frequency dependence of the spectral noise density (S<sub>I</sub>) for Ni/4H-SiC SBDs with C/Si = 0.9 at room temperature under <span class="html-italic">V<sub>R</sub></span> = −10~−200 V, the inset shows the bias voltage dependence of the spectral noise density at 1K Hz; (<b>d</b>) Noise spectra of Ni/4H-SiC SBDs with C/Si ratios (C/Si = 0.9, 1 or 1.1).</p> Full article ">Figure 4
<p>(<b>a</b>) Deep level transient spectrum testing (DLTS) spectra of Ni/4H-SiC SBD with C/Si = 0.9; (<b>b</b>) The Z<sub>1/2</sub> defect concentration of Ni/4H-SiC SBDs under different CVD growth conditions. The inset shows the dependence of the reverse current density under <span class="html-italic">V<sub>R</sub></span> = −200 V (red square symbols) and breakdown voltage (blue triangle symbols) on Z<sub>1/2</sub> defect concentration for Ni/4H-SiC SBDs with C/Si ratios (C/Si = 0.9, 1 or 1.1).</p> Full article ">Figure 5
<p>(<b>a</b>) Atomic force microscopy (AFM) images and (<b>b</b>) PL spectra of 4H-SiC epilayers with C/Si ratios (C/Si = 0.9, 1 or 1.1).</p> Full article ">
12 pages, 6083 KiB  
Article
Microfluidic Droplet-Storage Array
by Hoon Suk Rho and Han Gardeniers
Micromachines 2020, 11(6), 608; https://doi.org/10.3390/mi11060608 - 23 Jun 2020
Cited by 6 | Viewed by 4200
Abstract
A microfluidic droplet-storage array that is capable of the continuous operation of droplet formation, storing, repositioning, retrieving, injecting and restoring is demonstrated. The microfluidic chip comprised four valve-assisted droplet generators and a 3 × 16 droplet-storage array. The integrated pneumatically actuated microvalves enable [...] Read more.
A microfluidic droplet-storage array that is capable of the continuous operation of droplet formation, storing, repositioning, retrieving, injecting and restoring is demonstrated. The microfluidic chip comprised four valve-assisted droplet generators and a 3 × 16 droplet-storage array. The integrated pneumatically actuated microvalves enable the precise control of aqueous phase dispensing, as well as carrier fluid flow path and direction for flexible manipulating water-in-oil droplets in the chip. The size of droplets formed by the valve-assisted droplet generators was validated under various operating conditions such as pressures for introducing solutions and dispensing time. In addition, flexible droplet addressing in the storage array was demonstrated by storing droplets with various numbers and compositions in different storage units as well as rearranging their stored positions. Moreover, serial injections of new droplets into a retrieved droplet from a storage unit was performed to show the potential of the platform in sequential dosing on incubated droplet-based reactors at the desired timeline. The droplet-storage array with great freedom and flexibility in droplet handling could be applied for performing complex chemical and biologic reactions, especially in which incubation and dosing steps are necessary. Full article
(This article belongs to the Special Issue Droplet Microfluidics)
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Figure 1

Figure 1
<p>Design and operation of the microfluidic droplet-storage array. A computer-aided design shows the integration of 4 droplet generators and 48 droplet-storage units; (<b>A</b>) process flow of the droplet generation by using a microfluidic valve; (<b>B</b>) fluid flow direction control by switching a carrier fluid flow channel connection between the two sets of an inlet and an outlet; (<b>C</b>) valve operation to collect and isolate droplets in a droplet-storage unit.</p> Full article ">Figure 2
<p>The w/o droplet generation with a pneumatically actuated microfluidic valve; (<b>A</b>) Step-by-step procedures of droplet formation at the constant droplet generation condition (P<sub>water</sub>/P<sub>oil</sub> = 1 and dispensing time = 167 ms); (<b>B</b>) Droplet size-control by varying the dispensing time at the constant fluid flow condition (Pwater/Poil = 1). Images captured from a recorded movie. Scale bars: 400 µm; (<b>C</b>) relationship between the dispensing time and the volume of formed droplets at various fluid flow conditions (n = 20).</p> Full article ">Figure 3
<p>Droplet addressing in the storage unit array. (<b>A</b>) Nine sets of three droplets were isolated in a 3 × 3 storage unit array with random orders in droplet colors. (<b>B</b>–<b>E</b>) By moving the droplets with the control of carrier fluid flow direction as well as droplet moving path, (<b>F</b>) the color orders of droplets in each row rearranged to blue, red and yellow. Scale bars: 500 µm.</p> Full article ">Figure 4
<p>Serial injection of droplets into the target droplet in the droplet generator; (<b>A</b>) Process flow of the serial injection by changing the flow direction of the carrier fluid. Scale bars: 500 µm; (<b>B</b>) sequential dilution of RITC-dextran droplet (initial concentration of 1 g/L) by adding multiple Milli-Q water droplets (n = 3).</p> Full article ">Figure 5
<p>Continuous processes of (<b>A</b>) droplet formation and storing, (<b>B</b>) repositioning and (<b>C</b>) injection and restoring. Scale bars: 1 mm.</p> Full article ">
15 pages, 2314 KiB  
Article
Acoustic Streaming Generated by Sharp Edges: The Coupled Influences of Liquid Viscosity and Acoustic Frequency
by Chuanyu Zhang, Xiaofeng Guo, Laurent Royon and Philippe Brunet
Micromachines 2020, 11(6), 607; https://doi.org/10.3390/mi11060607 - 22 Jun 2020
Cited by 24 | Viewed by 4269
Abstract
Acoustic streaming can be generated around sharp structures, even when the acoustic wavelength is much larger than the vessel size. This sharp-edge streaming can be relatively intense, owing to the strongly focused inertial effect experienced by the acoustic flow near the tip. We [...] Read more.
Acoustic streaming can be generated around sharp structures, even when the acoustic wavelength is much larger than the vessel size. This sharp-edge streaming can be relatively intense, owing to the strongly focused inertial effect experienced by the acoustic flow near the tip. We conducted experiments with particle image velocimetry to quantify this streaming flow through the influence of liquid viscosity ν , from 1 mm 2 /s to 30 mm 2 /s, and acoustic frequency f from 500 Hz to 3500 Hz. Both quantities supposedly influence the thickness of the viscous boundary layer δ = ν π f 1 / 2 . For all situations, the streaming flow appears as a main central jet from the tip, generating two lateral vortices beside the tip and outside the boundary layer. As a characteristic streaming velocity, the maximal velocity is located at a distance of δ from the tip, and it increases as the square of the acoustic velocity. We then provide empirical scaling laws to quantify the influence of ν and f on the streaming velocity. Globally, the streaming velocity is dramatically weakened by a higher viscosity, whereas the flow pattern and the disturbance distance remain similar regardless of viscosity. Besides viscosity, the frequency also strongly influences the maximal streaming velocity. Full article
(This article belongs to the Special Issue Acoustofluidics)
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Figure 1

Figure 1
<p>Left—Sketch of the experimental setup. A piezoelectric transducer is glued on a glass microscope slide, which is used as a coverslip for a PDMS microchannel with one or several sharp-edge structures. The transducer is supplied with a function generator and a home-made amplifier, adjusted by the peak-to-peak voltage monitored with an oscilloscope. The fluid seeded with fluorescent particles is brought by a syringe pump through two inlets. The flow inside the microchannel is visualised by a high-speed camera connected to a binocular microscope. Right —The piezo-transducer generates an acoustic wave within the Y-shaped channel. In the vicinity of the sharp-edge structure, the acoustic wave generates a streaming flow.</p> Full article ">Figure 2
<p>(<b>a</b>) Geometry of the microchannel and sharp-edge. (<b>b</b>) Trajectories of individual particles (diameter 4.9 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m), over several periods, for the left-hand-side zoom-in image. The frame per second (fps) equals <math display="inline"><semantics> <mrow> <mn>4</mn> <mi>f</mi> </mrow> </semantics></math> = 10,000 fps; for the right-hand-side one, the fps equals <math display="inline"><semantics> <mrow> <mn>10</mn> <mi>f</mi> </mrow> </semantics></math> = 25,000 fps; the two images have the same exposure time <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>/</mo> <mo>(</mo> <mn>10</mn> <mi>f</mi> <mo>)</mo> <mo>=</mo> <mn>1</mn> <mo>/</mo> <mn>25</mn> <mo>,</mo> <mn>000</mn> </mrow> </semantics></math> s. Far from the tip, the flow is oscillating at frequency <span class="html-italic">f</span> and amplitude <span class="html-italic">A</span>, as testified by the segment described by each particle. Close to the tip, the trajectories of the particles show a superposition of oscillations with higher amplitude due to the sharp edge and advection due to the intense streaming flow.</p> Full article ">Figure 3
<p>Streaming velocity field <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi>s</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> from PIV measurements, with different liquid viscosities. <span class="html-italic">f</span> = 2500 Hz and <math display="inline"><semantics> <msub> <mi>V</mi> <mi>a</mi> </msub> </semantics></math> = 35 mm/s. (<b>a</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 1.158 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s, (<b>b</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 4.32 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s, (<b>c</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 13.75 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s, (<b>d</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 29.44 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s. Scales are the same for the four cases.</p> Full article ">Figure 4
<p>Vorticity maps of the streaming fields corresponding to the cases of <a href="#micromachines-11-00607-f003" class="html-fig">Figure 3</a>a–d, with corresponding colour bars that emphasise the decrease of vorticity. <span class="html-italic">f</span> = 2500 Hz and <math display="inline"><semantics> <msub> <mi>V</mi> <mi>a</mi> </msub> </semantics></math> = 35 mm/s. (<b>a</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 1.158 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s, (<b>b</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 4.32 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s, (<b>c</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 13.75 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s, (<b>d</b>) <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 29.44 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s. Dotted lines show the boundaries of the sharp edge.</p> Full article ">Figure 5
<p>Streaming velocity profile along vertical direction <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi>s</mi> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, for three different viscosities (Fluids 2, 3 and 4 with <math display="inline"><semantics> <mi>ν</mi> </semantics></math> respectively equal to 1.158, 4.32 and 13.75 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s). The operation condition is at frequency <span class="html-italic">f</span>= 2500 Hz and acoustic velocity <math display="inline"><semantics> <msub> <mi>V</mi> <mi>a</mi> </msub> </semantics></math> = 35 mm/s. Additionally labelled are the values of the VBL thickness for the three fluids <math display="inline"><semantics> <msub> <mi>δ</mi> <mn>2</mn> </msub> </semantics></math>, <math display="inline"><semantics> <msub> <mi>δ</mi> <mn>3</mn> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>δ</mi> <mn>4</mn> </msub> </semantics></math>. The inset plots the same data in Lin-log axes.</p> Full article ">Figure 6
<p>Left —Maximal streaming velocity <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi mathvariant="normal">s</mi> </msub> <mspace width="4.pt"/> <mi>max</mi> </mrow> </semantics></math> versus the square of the acoustic forcing velocity <math display="inline"><semantics> <msubsup> <mi>V</mi> <mi>a</mi> <mn>2</mn> </msubsup> </semantics></math>, for different liquid viscosities <math display="inline"><semantics> <mi>ν</mi> </semantics></math>, indicated in <a href="#micromachines-11-00607-t002" class="html-table">Table 2</a>. Right—Quantity <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi mathvariant="normal">s</mi> </msub> <mspace width="4.pt"/> <mi>max</mi> <mo>×</mo> <msup> <mi>ν</mi> <mrow> <mo>−</mo> <mi>a</mi> </mrow> </msup> </mrow> </semantics></math>, with <span class="html-italic">a</span>= −0.9. Inset <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi mathvariant="normal">s</mi> </msub> <mspace width="4.pt"/> <mi>max</mi> <mo>×</mo> <msup> <mi>ν</mi> <mrow> <mn>1</mn> <mo>/</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>. All measurements were obtained at <span class="html-italic">f</span> = 2500 Hz. The averaged typical error bar is indicated.</p> Full article ">Figure 7
<p>Streaming velocity field <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi>s</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> from PIV measurements, with different excitation frequencies <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 4.32 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s (Fluid 3) and <math display="inline"><semantics> <msub> <mi>V</mi> <mi>a</mi> </msub> </semantics></math> = 22.4 mm/s. (<b>a</b>) <span class="html-italic">f</span> = 3500 Hz, (<b>b</b>) <span class="html-italic">f</span> = 2500 Hz, (<b>c</b>) <span class="html-italic">f</span> = 1250 Hz, (<b>d</b>) <span class="html-italic">f</span> = 800 Hz. Scales are the same for the four cases.</p> Full article ">Figure 8
<p>Vorticity maps of the streaming fields corresponding to the cases of <a href="#micromachines-11-00607-f007" class="html-fig">Figure 7</a>a–d. <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 4.32 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s (Fluid 3) and <math display="inline"><semantics> <msub> <mi>V</mi> <mi>a</mi> </msub> </semantics></math> = 22.4 mm/s. (<b>a</b>) <span class="html-italic">f</span> = 3500 Hz, (<b>b</b>) <span class="html-italic">f</span> = 2500 Hz, (<b>c</b>) <span class="html-italic">f</span> = 1250 Hz, (<b>d</b>) <span class="html-italic">f</span> = 800 Hz. Dotted lines show the boundaries of the sharp edge.</p> Full article ">Figure 9
<p>Streaming velocity profile along vertical direction <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi>s</mi> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, for four different frequencies. Liquid viscosity <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 4.32 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s and <math display="inline"><semantics> <msub> <mi>V</mi> <mi>a</mi> </msub> </semantics></math> = 22 mm/s. The inset plots the same data in Lin-log axes.</p> Full article ">Figure 10
<p>Maximal streaming velocity <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi mathvariant="normal">s</mi> </msub> <mspace width="0.166667em"/> <mi>max</mi> </mrow> </semantics></math> versus <math display="inline"><semantics> <msubsup> <mi>V</mi> <mi>a</mi> <mn>2</mn> </msubsup> </semantics></math>, for different <span class="html-italic">f</span> and the same viscosity <math display="inline"><semantics> <mi>ν</mi> </semantics></math> = 4.32 mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>/s. The dashed-dotted line suggests a linear relationship, with a prefactor <math display="inline"><semantics> <mi>θ</mi> </semantics></math> = 5×10<math display="inline"><semantics> <msup> <mrow/> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> </semantics></math> s/mm. The inset represents a magnified view of the plot for the lowest values of <math display="inline"><semantics> <msubsup> <mi>V</mi> <mi>a</mi> <mn>2</mn> </msubsup> </semantics></math>, suggesting a linear scaling with a prefactor <math display="inline"><semantics> <mi>θ</mi> </semantics></math> = 0.0011 s/mm.</p> Full article ">Figure 11
<p>Attempts of data rescalling for <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi mathvariant="normal">s</mi> </msub> <mspace width="0.166667em"/> <mi>max</mi> </mrow> </semantics></math> (<b>a</b>) versus <math display="inline"><semantics> <mrow> <msubsup> <mi>V</mi> <mi>a</mi> <mn>2</mn> </msubsup> <mo>×</mo> <mi>f</mi> </mrow> </semantics></math> (insert shows data in the lowest range of <math display="inline"><semantics> <msubsup> <mi>V</mi> <mi>a</mi> <mn>2</mn> </msubsup> </semantics></math>) and (<b>b</b>) versus <math display="inline"><semantics> <mrow> <msubsup> <mi>V</mi> <mi>a</mi> <mn>2</mn> </msubsup> <mo>×</mo> <msup> <mi>f</mi> <mrow> <mo>−</mo> <mn>1</mn> <mo>/</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math> showing a fair collapse of data.</p> Full article ">
18 pages, 2895 KiB  
Article
Environment-Sensitive Intelligent Self-Reproducing Artificial Cell with a Modification-Active Lipo-Deoxyribozyme
by Muneyuki Matsuo, Yuiko Hirata, Kensuke Kurihara, Taro Toyota, Toru Miura, Kentaro Suzuki and Tadashi Sugawara
Micromachines 2020, 11(6), 606; https://doi.org/10.3390/mi11060606 - 22 Jun 2020
Cited by 14 | Viewed by 3631
Abstract
As a supramolecular micromachine with information flow, a giant vesicle (GV)-based artificial cell that exhibits a linked proliferation between GV reproduction and internal DNA amplification has been explored in this study. The linked proliferation is controlled by a complex consisting of GV membrane-intruded [...] Read more.
As a supramolecular micromachine with information flow, a giant vesicle (GV)-based artificial cell that exhibits a linked proliferation between GV reproduction and internal DNA amplification has been explored in this study. The linked proliferation is controlled by a complex consisting of GV membrane-intruded DNA with acidic amphiphilic catalysts, working overall as a lipo-deoxyribozyme. Here, we investigated how a GV-based artificial cell containing this lipo-deoxyribozyme responds to diverse external and internal environments, changing its proliferative dynamics. We observed morphological changes (phenotypic expression) in GVs induced by the addition of membrane precursors with different intervals of addition (starvation periods). First, we focused on a new phenotype, the “multiple tubulated” form, which emerged after a long starvation period. Compared to other forms, the multiple tubulated form is characterized by a larger membrane surface with a heavily cationic charge. A second consideration is the effect of the chain length of encapsulated DNA on competitive proliferation. The competitive proliferation among three different species of artificial cells containing different lengths of DNA was investigated. The results clearly showed a distinct intervention in the proliferation dynamics of the artificial cells with each other. In this sense, our GV-based artificial cell can be regarded as an intelligent supramolecular machine responding to external and internal environments, providing a new concept for developing molecular machines and robotics. Full article
(This article belongs to the Special Issue Recent Advances of Molecular Machines and Molecular Robots)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Self-reproduction of GV-based artificial cells working as self-reproducing molecular machines (<b>a</b>). Relevant molecular structures. <b>V*</b> is a precursor of membrane lipids (nutrients), <b>V</b> is a membrane lipid, E is a water-soluble electrolyte, and <b>C</b> is an amphiphilic catalyst (<b>b</b>). DNA amplification in GV-based artificial cells and the formation of <b>C</b>@DNA and its proliferation induced by the addition of <b>V*</b> (<b>c</b>). Artificial cells exhibiting phenotypic plasticity depending on starvation time (<b>d</b>). Competitive proliferation between GVs incorporating different DNA lengths. Red double helices represent short DNA and blue double ones represent long DNA (<b>e</b>).</p> Full article ">Figure 2
<p>Two patterns of morphological changes observed by the addition of <b>V*</b> after starvation periods: DIC microscopy images of the budding (<b>a</b>), the time-lapse morphological changes to the multiple tubulation (<b>b</b>), followed by addition of membrane precursor <b>V*</b>. Scale bars represent 10 µm. Schematic illustration of the starvation period-dependent crossover from a normal group to a starved group (<b>c</b>), dependence of ratios of multiple tubulation to the whole morphologically changed GVs on the starvation periods. The ratio of multiple tubulation to total changes (multiple tubulation + budding) increased from 14% (2/14 protocells) after 3 h to 50% (3/6) after 15 h, and eventually saturated at ca. 65% (7/11), (4/6), (4/6) after 27, 39, and 51 h, respectively. The total number of GVs was obtained through 10 experiments. Error bars represent the confidence interval of 95% on the basis of the two-term distribution (<b>d</b>).</p> Full article ">Figure 3
<p>Intervesicular dynamics regarding coating pre-BD by MT. Confocal microscopy image of a mixed dispersion of MT tagged with BODIPY-HPC and pre-BD tagged with Texas Red-DHPE at 6 h after mixing (<b>a</b>), Confocal microscopy images of coated pre-BD with MT merged (channel), BODIPY channel, Texas Red channel, Scale bar represents 10 μm. (<b>b</b>, left, middle, right), Flow cytometry image of MT and pre-BD before addition of <b>V*</b>, image at 1 min after mixing, image at 3 h after mixing (<b>c</b>, left, middle, left). 3c left is a combination of two independent images separated by a diagonal white line. The above left image is assigned to the image of MT and the right below to the image of pre-BD before addition of <b>V*</b>.</p> Full article ">Figure 4
<p>Competitive proliferation of GV-based artificial cells containing DNA (L 3200, M 1164, and S 374 bp). The increase ratios of GVs were measured by confocal scanning laser microscopy. For GV(L) vs. GV(M): GV(L) membrane was tagged with BODIPY-HPC, and GV(M) membrane was tagged with Texas Red-DHPE (<b>a</b>), and for GV(M) vs. GV(S): GV(M) membrane was tagged with BODIPY-HPC, and GV(S) membrane was tagged with Texas Red-DHPE (<b>b</b>).</p> Full article ">Figure 5
<p>Flow cytometry diagrams showing the correlation between the diameters which is given by correlation with size of polystyrene beads (<a href="#app1-micromachines-11-00606" class="html-app">Figure S9</a>) and fluorescence intensities of GV(S) and GV(M) in competitive proliferation. The two diagrams in the left column (<b>a)</b> and (<b>c</b>) correspond to population changes of GV(S). The two diagrams in the right column (<b>b</b>) and (<b>d</b>) correspond to population changes of GV(M). The ratio of <b>V*</b> and total membrane lipids is 3:1 in the top row and 1:3 in the bottom row.</p> Full article ">Figure 6
<p>Phototactic movement of an oil droplet (<b>a</b>), a GV-based artificial cell (<b>b</b>), and a recursive GV-based artificial cell with four cellular phases (<b>c</b>).</p> Full article ">
12 pages, 5287 KiB  
Article
Characterization and Analysis of Metal Adhesion to Parylene Polymer Substrate Using Scotch Tape Test for Peripheral Neural Probe
by Seonho Seok, HyungDal Park and Jinseok Kim
Micromachines 2020, 11(6), 605; https://doi.org/10.3390/mi11060605 - 22 Jun 2020
Cited by 12 | Viewed by 4306
Abstract
This paper presents measurement and FEM (Finite Element Method) analysis of metal adhesion force to a parylene substrate for implantable neural probe. A test device composed of 300 nm-thick gold and 30 nm-thick titanium metal electrodes on top of parylene substrate was prepared. [...] Read more.
This paper presents measurement and FEM (Finite Element Method) analysis of metal adhesion force to a parylene substrate for implantable neural probe. A test device composed of 300 nm-thick gold and 30 nm-thick titanium metal electrodes on top of parylene substrate was prepared. The metal electrodes suffer from delamination during wet metal patterning process; thus, CF4 plasma treatment was applied to the parylene substrate before metal deposition. The two thin film metal layers were deposited by e-beam evaporation process. Metal electrodes had 200 μm in width, 300 μm spacing between the metal lines, and 5 mm length as the neural probe. Adhesion force of the metal lines to parylene substrate was measured with scotch tape test. Angle between the scotch tape and the test device substrate changed from 60° to 90° during characterization. Force exerted the scotch tape was recorded as the function of displacement of the scotch tape. It was found that a peak was created in measured force-displacement curve due to metal delamination. Metal adhesion was estimated 1.3 J/m2 by referring to the force peak and metal width at the force-displacement curve. Besides, the scotch tape test was simulated to comprehend delamination behavior of the test through FEM modeling. Full article
(This article belongs to the Special Issue MEMS Packaging Technologies and 3D Integration)
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Figure 1
<p>Design of test pattern.</p> Full article ">Figure 2
<p>Test sample fabrication process.</p> Full article ">Figure 3
<p>Parylene surface modification.</p> Full article ">Figure 4
<p>Test samples fabricated on 4-inch silicon substrate.</p> Full article ">Figure 5
<p>Scotch tape test for metal adhesion to parylene substrates.</p> Full article ">Figure 6
<p>Force-displacement curves from scotch tape test with metal lines on parylene substrate.</p> Full article ">Figure 7
<p>Force-displacement curves from scotch tape test with metal lines on parylene substrate with CF<sub>4</sub> treatment.</p> Full article ">Figure 8
<p>Tensile test result of scotch tape.</p> Full article ">Figure 9
<p>Crack propagation model and simulation results.</p> Full article ">Figure 9 Cont.
<p>Crack propagation model and simulation results.</p> Full article ">Figure 10
<p>Three-dimensional Finite Element Method (FEM) model for Cohesive Zone model (CZM) interface delamination.</p> Full article ">Figure 10 Cont.
<p>Three-dimensional Finite Element Method (FEM) model for Cohesive Zone model (CZM) interface delamination.</p> Full article ">Figure 11
<p>Force-displacement curves as function of metal width.</p> Full article ">
13 pages, 3796 KiB  
Article
Multi-Color Enhanced Fluorescence Imaging of a Breast Cancer Cell with A Hole-Arrayed Plasmonic Chip
by Makiko Yoshida, Hinako Chida, Fukiko Kimura, Shohei Yamamura and Keiko Tawa
Micromachines 2020, 11(6), 604; https://doi.org/10.3390/mi11060604 - 22 Jun 2020
Cited by 10 | Viewed by 3195
Abstract
Breast cancer cells of MDA-MB-231 express various types of membrane proteins in the cell membrane. In this study, two types of membrane proteins in MDA-MB-231 cells were observed using a plasmonic chip with an epifluorescence microscope. The targeted membrane proteins were epithelial cell [...] Read more.
Breast cancer cells of MDA-MB-231 express various types of membrane proteins in the cell membrane. In this study, two types of membrane proteins in MDA-MB-231 cells were observed using a plasmonic chip with an epifluorescence microscope. The targeted membrane proteins were epithelial cell adhesion molecules (EpCAMs) and epidermal growth factor receptor (EGFR), and Alexa®488-EGFR antibody and allophycocyanin (APC)-labeled EpCAM antibody were applied to the fluorescent detection. The plasmonic chip used in this study is composed of a two-dimensional hole-array structure, which is expected to enhance the fluorescence at different resonance wavelengths due to two kinds of grating pitches in a square side and a diagonal direction. As a result of multi-color imaging, the enhancement factor of Alexa®488-EGFR and APC-EpCAM was 13 ± 2 and 12 ± 2 times greater on the plasmonic chip, respectively. The excited wavelength or emission wavelength of each fluorescent agent is due to consistency with plasmon resonance wavelength in the hole-arrayed chip. The multi-color fluorescence images of breast cancer cells were improved by the hole-arrayed plasmonic chip. Full article
(This article belongs to the Special Issue Micro and Nano Devices for Cell Analysis)
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<p>Schematic of <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mi>g</mi> </msub> </mrow> </semantics></math> vectors in a hole-arrayed plasmonic chip. The red and blue arrows correspond to <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> <mn>45</mn> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math>, respectively.</p> Full article ">Figure 2
<p>Schematic of a brief concept in this study.</p> Full article ">Figure 3
<p>(<b>a</b>) An atomic force microscopy (AFM) image of a plasmonic chip with a hole-arrayed structure. (<b>b</b>) A cross-sectional view of the periodic structure.</p> Full article ">Figure 4
<p>Bright field images (<b>a</b>,<b>d</b>), Alexa<sup>®</sup>488-EGFR fluorescence images (<b>b</b>,<b>e</b>), and allophycocyanin (APC)-epithelial cell adhesion molecule (EpCAM) fluorescence images (<b>c</b>,<b>f</b>) for MDA-MB-231 cells. The upper panels (<b>a</b>–<b>c</b>) and the lower panels (<b>d</b>–<b>f</b>) show the images taken on the plasmonic chip with a 30 nm- and a 80 nm-thick SiO<sub>2</sub> layer, respectively. The max-min intensities that express the brightness contrast in fluorescence images of Alexa<sup>®</sup>488-EGFR and APC-EpCAM were adjusted to lie within the range of 3100 and 900 counts/s, respectively. Bars correspond to 10 μm.</p> Full article ">Figure 4 Cont.
<p>Bright field images (<b>a</b>,<b>d</b>), Alexa<sup>®</sup>488-EGFR fluorescence images (<b>b</b>,<b>e</b>), and allophycocyanin (APC)-epithelial cell adhesion molecule (EpCAM) fluorescence images (<b>c</b>,<b>f</b>) for MDA-MB-231 cells. The upper panels (<b>a</b>–<b>c</b>) and the lower panels (<b>d</b>–<b>f</b>) show the images taken on the plasmonic chip with a 30 nm- and a 80 nm-thick SiO<sub>2</sub> layer, respectively. The max-min intensities that express the brightness contrast in fluorescence images of Alexa<sup>®</sup>488-EGFR and APC-EpCAM were adjusted to lie within the range of 3100 and 900 counts/s, respectively. Bars correspond to 10 μm.</p> Full article ">Figure 5
<p>Bright field images (<b>a</b>,<b>d</b>), Alexa<sup>®</sup>488-EGFR fluorescence images (<b>b</b>,<b>e</b>), and APC-EpCAM images (<b>c</b>,<b>f</b>) for MDA-MB-231 cells. The upper panels (<b>a</b>–<b>c</b>) and the lower panels (<b>d</b>–<b>f</b>) show the images taken on the coverslip and plasmonic chip, respectively. The max-min intensities that express the brightness contrast in fluorescence images of Alexa<sup>®</sup>488-EGFR and APC-EpCAM were adjusted to lie within the range of 3400 and 1200 counts/s, respectively. Bars correspond to 10 μm.</p> Full article ">Figure 6
<p>Enhancement factor for the four sheets of a plasmonic chip. The green and red bars correspond to the values for Alexa<sup>®</sup>488-EGFR and APC-EpCAM, respectively.</p> Full article ">Figure 7
<p>Reflection spectra and resonance wavelengths calculated from the resonance condition. (<b>a</b>) Reflection spectra measured by microspectroscopy. Two dips were confirmed at the position of the theoretically expected resonance wavelength. (<b>b</b>) The resonance wavelength at the water interface in a 500 nm pitch hole-arrayed plasmonic chip. The blue and red solid lines indicate <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> <mn>45</mn> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math>, respectively, and the intersection of the blue and red solid lines with the <span class="html-italic">k<sub>spp</sub></span> curve are the theoretical resonance wavelength.</p> Full article ">Figure 7 Cont.
<p>Reflection spectra and resonance wavelengths calculated from the resonance condition. (<b>a</b>) Reflection spectra measured by microspectroscopy. Two dips were confirmed at the position of the theoretically expected resonance wavelength. (<b>b</b>) The resonance wavelength at the water interface in a 500 nm pitch hole-arrayed plasmonic chip. The blue and red solid lines indicate <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> <mn>45</mn> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math>, respectively, and the intersection of the blue and red solid lines with the <span class="html-italic">k<sub>spp</sub></span> curve are the theoretical resonance wavelength.</p> Full article ">Figure 8
<p>Resonance angle spectra calculated from the theoretical resonance condition at the water interface every 10° of the azimuth angle φ: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> of Bull’s eye type with 400 nm pitch; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> of hole-arrayed type with 500 nm pitch; and (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> <mn>45</mn> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> of hole-arrayed type with 500 nm pitch. φ = 0 (black solid line), 10 (black broken line), 20 (blue solid line), 30 (blue broken line), 40 (green solid line), 50 (green broken line), 60 (orange solid line), 70 (orange broken line), 80 (red solid line), and 90 (red broken line). The green and red bands correspond to the excitation wavelength range and the emission range of the GFP and Cy5 filters, respectively.</p> Full article ">Figure 8 Cont.
<p>Resonance angle spectra calculated from the theoretical resonance condition at the water interface every 10° of the azimuth angle φ: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> of Bull’s eye type with 400 nm pitch; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> of hole-arrayed type with 500 nm pitch; and (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>g</mi> <mi>x</mi> <mn>45</mn> </mrow> </msub> <msup> <mrow/> <mrow> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mo stretchy="false">)</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> of hole-arrayed type with 500 nm pitch. φ = 0 (black solid line), 10 (black broken line), 20 (blue solid line), 30 (blue broken line), 40 (green solid line), 50 (green broken line), 60 (orange solid line), 70 (orange broken line), 80 (red solid line), and 90 (red broken line). The green and red bands correspond to the excitation wavelength range and the emission range of the GFP and Cy5 filters, respectively.</p> Full article ">
34 pages, 10190 KiB  
Review
Droplet and Particle Generation on Centrifugal Microfluidic Platforms: A Review
by Javid Azimi-Boulali, Masoud Madadelahi, Marc J. Madou and Sergio O. Martinez-Chapa
Micromachines 2020, 11(6), 603; https://doi.org/10.3390/mi11060603 - 22 Jun 2020
Cited by 27 | Viewed by 6920
Abstract
The use of multiphase flows in microfluidics to carry dispersed phase material (droplets, particles, bubbles, or fibers) has many applications. In this review paper, we focus on such flows on centrifugal microfluidic platforms and present different methods of dispersed phase material generation. These [...] Read more.
The use of multiphase flows in microfluidics to carry dispersed phase material (droplets, particles, bubbles, or fibers) has many applications. In this review paper, we focus on such flows on centrifugal microfluidic platforms and present different methods of dispersed phase material generation. These methods are classified into three specific categories, i.e., step emulsification, crossflow, and dispenser nozzle. Previous works on these topics are discussed and related parameters and specifications, including the size, material, production rate, and rotational speed are explicitly mentioned. In addition, the associated theories and important dimensionless numbers are presented. Finally, we discuss the commercialization of these devices and show a comparison to unveil the pros and cons of the different methods so that researchers can select the centrifugal droplet/particle generation method which better suits their needs. Full article
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<p>Different methods of droplet/particle generation on centrifugal microfluidic platforms.</p> Full article ">Figure 2
<p>A schematic view of the step emulsification method.</p> Full article ">Figure 3
<p>(<b>A</b>) A microscope image of multiple nozzles producing homogeneous droplets. Reprinted with permission from [<a href="#B31-micromachines-11-00603" class="html-bibr">31</a>]; (<b>B</b>) Step emulsification and bubble removal design in PCR chamber. Reprinted with permission from [<a href="#B111-micromachines-11-00603" class="html-bibr">111</a>].</p> Full article ">Figure 4
<p>(<b>A</b>) Centrifugal force packs droplets together to form a hexagonal pattern by removing excess oil, and consequently, achieving high-volume fractions [<a href="#B109-micromachines-11-00603" class="html-bibr">109</a>]; (<b>B</b>) Stroboscopic images of the detachment process at the nozzle for the dripping and jetting regimes in centrifugal step emulsification in which high buoyancy at high Bo numbers support rapid breakup process and monodisperse droplets. Reprinted with permission from [<a href="#B47-micromachines-11-00603" class="html-bibr">47</a>].</p> Full article ">Figure 5
<p>(<b>A</b>) Principal of step emulsification in a centrifugal system. (<b>B</b>) Microscope image of produced droplets at 1000 g (scale bar 50 µm); (<b>C</b>) Diameter distribution of the produced droplets; (<b>D</b>) Effect of the level of oil phase to droplet diameter; (<b>E</b>) Effect of centrifugal force to droplet diameter. Reprinted with permission from [<a href="#B73-micromachines-11-00603" class="html-bibr">73</a>]; (<b>F</b>) Droplet generation in stationary carrier phase. Reprinted with permission from [<a href="#B43-micromachines-11-00603" class="html-bibr">43</a>].</p> Full article ">Figure 6
<p>Schematic view of the dispenser nozzle method for droplet and particle generation. Droplets are produced at the tip of the nozzle and enter a tube containing a continuous phase.</p> Full article ">Figure 7
<p>(<b>A</b>–<b>C</b>) Microscope images of beads. (A) 2% uniform particles of chitosan at 20 Hz; (B) 2% particles of chitosan at 25 Hz, smaller droplets retaining spherical shape; (C) 3% tear-like shape chitosan at 30 Hz; (<b>D</b>) Bead production rate at different rotational frequencies; (<b>E</b>) Size distribution histogram at 20 and 44 Hz with 2% chitosan. Reprinted with permission from [<a href="#B115-micromachines-11-00603" class="html-bibr">115</a>].</p> Full article ">Figure 8
<p>(<b>A</b>–<b>C</b>) Microbeads produced by different concentrations (4, 5, and 6 wt%) of Na-alginate solution; (<b>D</b>) Cell vitality before and after encapsulation (PC12). Reprinted with permission from [<a href="#B42-micromachines-11-00603" class="html-bibr">42</a>].</p> Full article ">Figure 9
<p>(<b>A</b>) Microchannel array (MiCA) fabrication and characteristics; (<b>B</b>) Acid-soluble fibers within the bundles; (<b>C</b>–<b>H</b>) Microscope images of the produced droplets in various centrifugal accelerations; (<b>I</b>) Morphology and size of droplets generated at various centrifugal accelerations. Reprinted with permission from [<a href="#B64-micromachines-11-00603" class="html-bibr">64</a>].</p> Full article ">Figure 10
<p>(<b>A</b>–<b>C</b>) Fluorescence images of produced polymeric particles by adjusting the airgap (L); (<b>D</b>) Effect of the airgap distance (L) on the deformation of the particles (D) in different Na-alginate concentrations; (<b>E</b>,<b>F</b>) Production of Janus particles on centrifugal microfluidics; (<b>G</b>,<b>H</b>) Production of magnetic Janus particles; (<b>I</b>) Manipulation of magnetic Janus particles with a magnet. Reprinted with permission from [<a href="#B79-micromachines-11-00603" class="html-bibr">79</a>].</p> Full article ">Figure 11
<p>(<b>A</b>–<b>C</b>) Microscope images of produced particles at different acceleration corresponding to different regimes. (<b>A</b>) Dripping without satellites; (<b>B</b>) Dripping with satellites; and (<b>C</b>) Jetting; (<b>D</b>) Experimental phase diagram showing different break-offs of droplets as a function of rotational speed and Na-alginate concentration; (<b>E</b>) Illustration of different pinch-off regimes. Microscope images of particles at different accelerations. Reprinted with permission from [<a href="#B69-micromachines-11-00603" class="html-bibr">69</a>].</p> Full article ">Figure 12
<p>(<b>A</b>,<b>B</b>) Conceptual illustration of oil-free production of monodisperse Ca-alginate particles with a by-pass channel and waste chamber for transferring spilled solution in order to keep the CaCl<sub>2</sub> solution level constant; (<b>C</b>) Diameter distribution of Ca-alginate particles. Reprinted with permission from [<a href="#B121-micromachines-11-00603" class="html-bibr">121</a>].</p> Full article ">Figure 13
<p>A schematic view of the crossflow mechanism of droplet generation on lab-on-a-disk (LOD) devices.</p> Full article ">Figure 14
<p>(<b>A</b>) Identification of three droplet structures depending on the channel geometry and rotational frequency; (<b>B</b>) Droplet splitting at the downstream in different frequencies. Reprinted with permission from [<a href="#B46-micromachines-11-00603" class="html-bibr">46</a>].</p> Full article ">Figure 15
<p>(<b>A</b>) Gas-bubble formation configuration; (<b>B</b>,<b>C</b>) Bubble generation by changing rotational speed to form various sizes with different intervals. Reprinted with permission from [<a href="#B127-micromachines-11-00603" class="html-bibr">127</a>].</p> Full article ">Figure 16
<p>(<b>A</b>) Configuration of droplet generation on a centrifugal microfluidic platform; (<b>B</b>) Water-in-oil droplet generation at 550 rpm the system. Scale bar 400 µm. Reprinted with permission from [<a href="#B55-micromachines-11-00603" class="html-bibr">55</a>]; (<b>C</b>) Schematic illustration of droplet generation with syringe reservoirs; (<b>D</b>) Flow focusing configuration platform for droplet generation; (<b>E</b>) A comparison of monodispersity between the results of a syringe pump (lower figure) and centrifugal system (upper figure). Reprinted with permission from [<a href="#B62-micromachines-11-00603" class="html-bibr">62</a>].</p> Full article ">Figure 17
<p>(<b>A</b>–<b>C</b>) The dynamics of flow in four different channels inside binary chip; channel A is azimuthal, channel B is diagonal, channels C and D are slanted; (<b>A</b>) Initial state; (<b>B</b>) LEFT state; (<b>C</b>) RIGTH state. (<b>D</b>,<b>E</b>) Producing droplet with binary chip. (<b>D</b>) Design of a binary chip with two reservoirs at the left and right, a metering chamber, a capillary valve, and a main channel; (<b>E</b>) In the LEFT state, the metering chamber is filled with liquid and the extra amount is directed to the left reservoir; (<b>F</b>) Increasing the rotating speed, the droplet breaks the capillary valve and enters to the main channel; (<b>G</b>) the extra amount of the liquid in the left reservoir returns back to the right reservoir. Reprinted with permission from [<a href="#B28-micromachines-11-00603" class="html-bibr">28</a>].</p> Full article ">Figure 18
<p>(<b>A</b>) Schematic of centrifugal homogenization device (CHD) in which a 20 mL syringe used as a reservoir and a nozzle dispenses the emulsions into the falcon tube cap. The whole system rotates at an angle of 45° to the rotation axis; (<b>B</b>) Schematic of the single-stage CHD with 2 mL reservoir; (<b>C</b>) Schematic of the double-stage reservoir with two reservoirs, i.e., a 2 mL and another 20 mL; (<b>D</b>–<b>F</b>) Microscope images of coarse pre-emulsion and resulting emulsions after homogenization at 4000 RPM and repeating the process 5 times. Reprinted with permission from [<a href="#B129-micromachines-11-00603" class="html-bibr">129</a>].</p> Full article ">Figure 19
<p>(<b>A</b>) The schematic of fluidic barrier concept; (<b>B</b>) The sequential images of the production of double emulsion on centrifugal microfluidics; (<b>C</b>) Microscope images of the particles using different frequencies and alginate concentrations. The scale bar is 500 μm; (<b>D</b>) Aspect ratio and diameter of the generated particles as a function of rotational frequency and alginate concentration. Reprinted with permission from [<a href="#B131-micromachines-11-00603" class="html-bibr">131</a>].</p> Full article ">
3 pages, 151 KiB  
Editorial
Editorial for the Special Issue on Particles Separation in Microfluidic Devices
by Naotomo Tottori and Takasi Nisisako
Micromachines 2020, 11(6), 602; https://doi.org/10.3390/mi11060602 - 22 Jun 2020
Viewed by 2218
Abstract
The separation and sorting of micro- and nano-sized particles is an important step in chemical, biological, and medical analyses [...] Full article
(This article belongs to the Special Issue Particles Separation in Microfluidic Devices)
3 pages, 155 KiB  
Editorial
Editorial of Special Issue “Nanostructured Light-Emitters”
by Hieu P. T. Nguyen
Micromachines 2020, 11(6), 601; https://doi.org/10.3390/mi11060601 - 21 Jun 2020
Cited by 3 | Viewed by 1998
Abstract
Significant progress has been made in the development of nanophotonic devices and the use of nanostructured materials for optoelectronic devices, including light-emitting diodes (LEDs) and laser diodes, has recently attracted tremendous attention due to the fact of their unique geometry [...] Full article
(This article belongs to the Special Issue Nanostructured Light-Emitters)
11 pages, 2661 KiB  
Article
Dynamically Tunable Phase Shifter with Commercial Graphene Nanoplatelets
by Muhammad Yasir and Patrizia Savi
Micromachines 2020, 11(6), 600; https://doi.org/10.3390/mi11060600 - 20 Jun 2020
Cited by 10 | Viewed by 2946
Abstract
In microwave frequency band the conductivity of graphene can be varied to design a number of tunable components. A tunable phase shifter based on commercial graphene nanoplatelets is introduced. The proposed configuration consists of a microstrip line with two stubs connected with a [...] Read more.
In microwave frequency band the conductivity of graphene can be varied to design a number of tunable components. A tunable phase shifter based on commercial graphene nanoplatelets is introduced. The proposed configuration consists of a microstrip line with two stubs connected with a taper. On each side of the stubs there is a gap, short circuited through a via, where the commercial graphene nanoplatelets are drop casted. By applying a DC bias voltage that alters the graphene resistance the phase of the transmitted signal through the microstrip line can be varied. In order to maximize the phase shift of the transmitted signal and minimize the insertion loss, the length of the taper and the stubs are optimized by the help of circuit model and full-wave simulations. A prototype working at 4GHz is fabricated and measured. A phase variation of 33 degrees is acquired with an amplitude variation of less than 0.4 dB. Full article
(This article belongs to the Special Issue Graphene based Electronic Devices)
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<p>FESEM images of the commercial graphene nanoplatelets. (<b>a</b>) multiple graphene flakes (<b>b</b>) individual flake.</p> Full article ">Figure 2
<p>Raman spectroscopy of the commercial graphene nanoplatelets.</p> Full article ">Figure 3
<p>(<b>a</b>) Two-port phase shifter circuital representation (<b>b</b>) Circuital representation of the stub.</p> Full article ">Figure 4
<p>Geometrical representation of the phase shifter with dimensions: (<b>a</b>) phase shifter; (<b>b</b>) individual stub.</p> Full article ">Figure 5
<p>S<sub>21</sub> versus R<sub>g</sub> for different L<sub>s</sub>: (<b>a</b>) amplitude variation; (<b>b</b>) phase variation.</p> Full article ">Figure 6
<p>Measurement setup of the commercial graphene based tunable phase shifter. In the inset a photograph of the prototype is shown.</p> Full article ">Figure 7
<p>Impact of the aspect ratio on the transmission: (<b>a</b>) Amplitude variation; (<b>b</b>) Phase variation.</p> Full article ">Figure 8
<p>Simulated transmission with different graphene resistance: (<b>a</b>) amplitude shift; (<b>b</b>) Phase shift.</p> Full article ">Figure 9
<p>Transmission coefficient with measured (solid lines) and simulated values (dashed lines): (<b>a</b>) Amplitude; (<b>b</b>) Phase.</p> Full article ">Figure 10
<p>Measured and simulated results at 4.3 GHz: (<b>a</b>) Insertion loss versus Rg; (<b>b</b>) Phase versus Rg.</p> Full article ">
31 pages, 3251 KiB  
Review
Evolution of Biochip Technology: A Review from Lab-on-a-Chip to Organ-on-a-Chip
by Neda Azizipour, Rahi Avazpour, Derek H. Rosenzweig, Mohamad Sawan and Abdellah Ajji
Micromachines 2020, 11(6), 599; https://doi.org/10.3390/mi11060599 - 18 Jun 2020
Cited by 179 | Viewed by 20835
Abstract
Following the advancements in microfluidics and lab-on-a-chip (LOC) technologies, a novel biomedical application for microfluidic based devices has emerged in recent years and microengineered cell culture platforms have been created. These micro-devices, known as organ-on-a-chip (OOC) platforms mimic the in vivo like microenvironment [...] Read more.
Following the advancements in microfluidics and lab-on-a-chip (LOC) technologies, a novel biomedical application for microfluidic based devices has emerged in recent years and microengineered cell culture platforms have been created. These micro-devices, known as organ-on-a-chip (OOC) platforms mimic the in vivo like microenvironment of living organs and offer more physiologically relevant in vitro models of human organs. Consequently, the concept of OOC has gained great attention from researchers in the field worldwide to offer powerful tools for biomedical researches including disease modeling, drug development, etc. This review highlights the background of biochip development. Herein, we focus on applications of LOC devices as a versatile tool for POC applications. We also review current progress in OOC platforms towards body-on-a-chip, and we provide concluding remarks and future perspectives for OOC platforms for POC applications. Full article
(This article belongs to the Special Issue Microengineering Techniques for Disease Modeling and Drug Discovery, Volume II)
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<p>Process of photolithography: (<b>a</b>) Spinning a photoresist to spread and heat up to evaporate any solvents, (<b>b</b>) irradiating with UV light through a photomask, (<b>c</b>) positive/negative tone. Figure is reproduced from the Reference [<a href="#B3-micromachines-11-00599" class="html-bibr">3</a>].</p> Full article ">Figure 2
<p>Laminar versus turbulent flow in the microfluidic channels. Figure is reproduced from Reference [<a href="#B44-micromachines-11-00599" class="html-bibr">44</a>].</p> Full article ">Figure 3
<p>Lateral flow assay schematic design: (<b>a</b>) A lateral flow test strip including sample inlet, sample layer, conjugate layer (i.e., reactive agents and detection molecules), incubation, detection zone and final absorbent layers including test and control lines (i.e., analyte detection and functionality test), (<b>b</b>) introduction of sample into the test strip via sample inlet, (<b>c</b>) antibodies conjugated to labeled nanoparticles start to bind to the analyte, (<b>d</b>) antibodies with antigens bind to the test line and antibodies without antigens bind to the control line. Reproduced from Reference [<a href="#B39-micromachines-11-00599" class="html-bibr">39</a>].</p> Full article ">Figure 4
<p>Blood glucose monitoring system: (<b>a</b>) Scheme of a commercial blood glucose test device, (<b>b</b>) different layers of a biosensor test strip. Reproduced from Reference [<a href="#B76-micromachines-11-00599" class="html-bibr">76</a>].</p> Full article ">Figure 5
<p>General process to fabricate a microfluidic OOC platform. Design, microfabrication, tissue culture and biological assays are the main steps to develop an OOC microfluidic platform for biological or pharmaceutical tests.</p> Full article ">Figure 6
<p>Schematic design of the microengineered lung-on-chip model developed by Huh et al. [<a href="#B12-micromachines-11-00599" class="html-bibr">12</a>]. An alveolar-capillary interface constructed on a flexible and porous PDMS membrane. By applying vacuum to the side chambers, a mechanical stretch has been created on the alveolar-capillary barrier to mimic a human breathing lung. Figure is reproduced from Reference [<a href="#B12-micromachines-11-00599" class="html-bibr">12</a>].</p> Full article ">Figure 7
<p>Schematic design of the heart-on-a-chip platform developed by Marsano et al. [<a href="#B92-micromachines-11-00599" class="html-bibr">92</a>]. This includes two microchambers which are divided by a PDMS membrane. The top chamber is subdivided into a central channel to grow 3D cell culture, and two side channels to refill culture media. The cardiac muscle’s contraction and relaxation mimicked through deformation of PDMS membrane by applying pressure on the bottom channel. Figure is reproduced from Reference [<a href="#B92-micromachines-11-00599" class="html-bibr">92</a>].</p> Full article ">Figure 8
<p>Brain tumor-on-a-chip model developed by Mimani et al. to access magnetic hyperthermia therapy on-a-chip. This chip was formed by a central and an external compartment separated by a porous interface. Magnetic nanoparticles through the central microfluidic channel introduced to central region of the chip which tumor cells have been cultivated in the 3D model. Then, through an alternating magnetic field, magnetic energy transforms to thermal energy and produce heat. Image reproduced from Reference [<a href="#B106-micromachines-11-00599" class="html-bibr">106</a>].</p> Full article ">
14 pages, 3895 KiB  
Article
Mobility Models Based on Forward Current-Voltage Characteristics of P-type Pseudo-Vertical Diamond Schottky Barrier Diodes
by Min-Woo Ha, Ogyun Seok, Hojun Lee and Hyun Ho Lee
Micromachines 2020, 11(6), 598; https://doi.org/10.3390/mi11060598 - 18 Jun 2020
Cited by 6 | Viewed by 3461
Abstract
Compared with silicon and silicon carbide, diamond has superior material parameters and is therefore suitable for power switching devices. Numerical simulation is important for predicting the electric characteristics of diamond devices before fabrication. Here, we present numerical simulations of p-type diamond pseudo-vertical Schottky [...] Read more.
Compared with silicon and silicon carbide, diamond has superior material parameters and is therefore suitable for power switching devices. Numerical simulation is important for predicting the electric characteristics of diamond devices before fabrication. Here, we present numerical simulations of p-type diamond pseudo-vertical Schottky barrier diodes using various mobility models. The constant mobility model, based on the parameter μconst, fixed the hole mobility absolutely. The analytic mobility model resulted in temperature- and doping concentration-dependent mobility. An improved model, the Lombard concentration, voltage, and temperature (CVT) mobility model, considered electric field-dependent mobility in addition to temperature and doping concentration. The forward voltage drop at 100 A/cm2 using the analytic and Lombard CVT mobility models was 2.86 and 5.17 V at 300 K, respectively. Finally, we used an empirical mobility model based on experimental results from the literature. We also compared the forward voltage drop and breakdown voltage of the devices, according to variations in p- drift layer thickness and cathode length. The device successfully achieved a low specific on-resistance of 6.8 mΩ∙cm2, a high breakdown voltage of 1190 V, and a high figure-of-merit of 210 MW/cm2. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Cross-sectional view of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) for forward current–voltage (I–V) and breakdown voltage. Simulated energy band at the Schottky contact/p- diamond drift layer at 300 K is also shown.</p> Full article ">Figure 2
<p>Forward current–voltage (I–V) characteristics of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) simulated using the constant mobility model at 300 K. The values of <span class="html-italic">μ<sub>const</sub></span> were 1000, 2000, 3000, and 4000 cm<sup>2</sup>/Vs, respectively. The metal work function, hole saturation velocity, and lattice temperature were 5.65 eV, 2.7 × 10<sup>7</sup> cm/s, and 300 K, respectively.</p> Full article ">Figure 3
<p>Forward current–voltage (I–V) characteristics of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) simulated using the constant mobility model at 200, 300, 400, and 500 K. The metal work function, hole saturation velocity, and <span class="html-italic">μ<sub>const</sub></span> were 5.65 eV, 2.7 × 10<sup>7</sup> cm/s, and 2000 cm<sup>2</sup>/Vs, respectively.</p> Full article ">Figure 4
<p>Forward current–voltage (I–V) characteristics of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) simulated using the analytic and Lombardi mobility models, respectively. The metal work function, hole saturation velocity, and lattice temperature were 5.65 eV, 2.7 × 10<sup>7</sup> cm/s, and 300 K, respectively.</p> Full article ">Figure 5
<p>Hole mobility of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) simulated using the analytic mobility model. The anode voltage (<span class="html-italic">V<sub>a</sub></span>) was 2 V at 300 K.</p> Full article ">Figure 6
<p>Hole mobility of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) simulated using the Lombardi CVT mobility model. The anode voltage (<span class="html-italic">V<sub>a</sub></span>) was 2 V at 300 K.</p> Full article ">Figure 7
<p>Hole mobility across the A-A’ section line of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) simulated using the analytic and Lombardi CVT mobility models. The metal work function, hole saturation velocity, lattice temperature, and anode voltage (<span class="html-italic">V<sub>a</sub></span>) were 5.65 eV, 2.7 × 10<sup>7</sup> cm/s, 300 K, and 2 V, respectively.</p> Full article ">Figure 8
<p>Forward current–voltage (I–V) of the p-type diamond pseudo-vertical Schottky barrier diode (SBD) simulated using the empirical mobility model at 300, 400, and 500 K. The metal work function, hole saturation velocity, hole mobility at 300 K, and <span class="html-italic">β</span> were 5.65 eV, 2.7 × 10<sup>7</sup> cm/s, 1990 cm<sup>2</sup>/Vs, and 3.092, respectively.</p> Full article ">Figure 9
<p>Simulated forward voltage drop at 100 A/cm<sup>2</sup> (<span class="html-italic">V<sub>f</sub></span>) and breakdown voltage of the p-type diamond pseudo-vertical Schottky barrier diodes (SBDs) with values of <span class="html-italic">t<sub>drift</sub></span> of 3.0, 4.0, 4.6, 5.0, and 6.0 μm. The empirical mobility model used for the forward current–voltage (I–V) characteristics at 300 K.</p> Full article ">Figure 10
<p>Simulated forward voltage drop at 100 A/cm<sup>2</sup> (<span class="html-italic">V<sub>f</sub></span>) and breakdown voltage of the p-type diamond pseudo-vertical Schottky barrier diodes (SBDs) with values of <span class="html-italic">l<sub>cathode</sub></span> of 0.5, 1.0, 2.0, and 3.0 μm. The empirical mobility model was used at 300 K.</p> Full article ">
17 pages, 5346 KiB  
Article
Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis
by Saifur Rahman, Abdullah S. Alwadie, Muhammed Irfan, Rabia Nawaz, Mohsin Raza, Ehtasham Javed and Muhammad Awais
Micromachines 2020, 11(6), 597; https://doi.org/10.3390/mi11060597 - 18 Jun 2020
Cited by 27 | Viewed by 6462
Abstract
Gas sensors are critical components when adhering to health safety and environmental policies in various manufacturing industries, such as the petroleum and oil industry; scent and makeup production; food and beverage manufacturing; chemical engineering; pollution monitoring. In recent times, gas sensors have been [...] Read more.
Gas sensors are critical components when adhering to health safety and environmental policies in various manufacturing industries, such as the petroleum and oil industry; scent and makeup production; food and beverage manufacturing; chemical engineering; pollution monitoring. In recent times, gas sensors have been introduced to medical diagnostics, bioprocesses, and plant disease diagnosis processes. There could be an adverse impact on human health due to the mixture of various gases (e.g., acetone (A), ethanol (E), propane (P)) that vent out from industrial areas. Therefore, it is important to accurately detect and differentiate such gases. Towards this goal, this paper presents a novel electronic nose (e-nose) detection method to classify various explosive gases. To detect explosive gases, metal oxide semiconductor (MOS) sensors are used as reliable tools to detect such volatile gases. The data received from MOS sensors are processed through a multivariate analysis technique to classify different categories of gases. Multivariate analysis was done using three variants—differential, relative, and fractional analyses—in principal components analysis (PCA). The MOS sensors also have three different designs: loading design, notch design, and Bi design. The proposed MOS sensor-based e-nose accurately detects and classifies three different gases, which indicates the reliability and practicality of the developed system. The developed system enables discrimination of these gases from the mixture. Based on the results from the proposed system, authorities can take preventive measures to deal with these gases to avoid their potential adverse impacts on employee health. Full article
(This article belongs to the Special Issue Future Wearable and Implants)
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<p>Block diagram of gases—data collection and classification.</p> Full article ">Figure 2
<p>Simulink model of classifying a mixture of gases for each sensor.</p> Full article ">Figure 3
<p>Time response of sensors based on metal oxide semiconductor (MOS) techniques for three various samples of volatile organic compounds (VOCs), each having three statistical records for the database (D).</p> Full article ">Figure 4
<p>Multivariate technique on organic gases for different feature loading designs.</p> Full article ">Figure 5
<p>Multivariate technique on organic gases for different feature notch design.</p> Full article ">Figure 6
<p>Multivariate technique on organic gases for different features in the Bi design.</p> Full article ">Figure 7
<p>Multivariate technique on organic gases fractional feature loading design.</p> Full article ">Figure 8
<p>Multivariate technique on organic gases fractional feature notch design.</p> Full article ">Figure 9
<p>Multivariate technique on organic gases fractional feature Bi design.</p> Full article ">Figure 10
<p>Multivariate technique on organic gases relative feature loading design.</p> Full article ">Figure 11
<p>Multivariate technique on organic gases relative feature notch design.</p> Full article ">Figure 12
<p>Multivariate technique on organic gases relative feature Bi design.</p> Full article ">
16 pages, 4781 KiB  
Article
A Graphene/Polycrystalline Silicon Photodiode and Its Integration in a Photodiode–Oxide–Semiconductor Field Effect Transistor
by Yu-Yang Tsai, Chun-Yu Kuo, Bo-Chang Li, Po-Wen Chiu and Klaus Y. J. Hsu
Micromachines 2020, 11(6), 596; https://doi.org/10.3390/mi11060596 - 17 Jun 2020
Cited by 4 | Viewed by 4321
Abstract
In recent years, the characteristics of the graphene/crystalline silicon junction have been frequently discussed in the literature, but study of the graphene/polycrystalline silicon junction and its potential applications is hardly found. The present work reports the observation of the electrical and optoelectronic characteristics [...] Read more.
In recent years, the characteristics of the graphene/crystalline silicon junction have been frequently discussed in the literature, but study of the graphene/polycrystalline silicon junction and its potential applications is hardly found. The present work reports the observation of the electrical and optoelectronic characteristics of a graphene/polycrystalline silicon junction and explores one possible usage of the junction. The current–voltage curve of the junction was measured to show the typical exponential behavior that can be seen in a forward biased diode, and the photovoltage of the junction showed a logarithmic dependence on light intensity. A new phototransistor named the “photodiode–oxide–semiconductor field effect transistor (PDOSFET)” was further proposed and verified in this work. In the PDOSFET, a graphene/polycrystalline silicon photodiode was directly merged on top of the gate oxide of a conventional metal–oxide–semiconductor field effect transistor (MOSFET). The magnitude of the channel current of this phototransistor showed a logarithmic dependence on the illumination level. It is shown in this work that the PDOSFET facilitates a better pixel design in a complementary metal–oxide–semiconductor (CMOS) image sensor, especially beneficial for high dynamic range (HDR) image detection. Full article
(This article belongs to the Special Issue Miniaturized Silicon Photodetectors: New Perspectives and Applications)
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<p>Samples of graphene/poly-Si junction. The graphene film partially covers the poly-Si in each sample.</p> Full article ">Figure 2
<p>Raman spectrum of the transferred graphene layer. It indicates that the graphene is a single layer with slight defects.</p> Full article ">Figure 3
<p>Measured total transmission rate of a typical graphene-on-glass sample. The transmission rate of the glass is about 96%.</p> Full article ">Figure 4
<p>Measured <span class="html-italic">I</span>–<span class="html-italic">V</span> curves of the graphene/n-type poly-Si junction. The voltage is applied to the graphene terminal and the poly-Si terminal is grounded.</p> Full article ">Figure 5
<p>Measured photovoltage of the graphene/n-type poly-Si junction photodiode (PD) under the illumination of a halogen lamp.</p> Full article ">Figure 6
<p>Conventional 3T pixel structure in a complementary-metal–oxide–semiconductor (CMOS) image sensor.</p> Full article ">Figure 7
<p>Proposed 3T pixel structure in a CMOS image sensor.</p> Full article ">Figure 8
<p>Schematic illustration of a graphene photodiode–oxide–semiconductor field effect transistor (PDOSFET) test device. Poly-Si gate thickness: 300 nm; gate oxide thickness: 20 nm; gate length: 6 μm.</p> Full article ">Figure 9
<p>Schematic illustration of the graphene transfer process in fabricating a PDOSFET.</p> Full article ">Figure 10
<p>Measured dark turn-on characteristic (<span class="html-italic">I<sub>d</sub></span>–<span class="html-italic">V<sub>g</sub></span> curve) of the PDOSFET; <span class="html-italic">V<sub>ds</sub></span> = 3.3 V.</p> Full article ">Figure 11
<p>Measured dark <span class="html-italic">I<sub>d</sub></span>–<span class="html-italic">V<sub>d</sub></span> curve of the PDOSFET under various gate bias voltages.</p> Full article ">Figure 12
<p>Measured PDOSFET source follower output voltage under various illuminance values.</p> Full article ">Figure 13
<p>Measured transient behavior of the output voltage (<span class="html-italic">V<sub>out</sub></span>) of the PDOSFET source follower with a loading resistance of 100 kΩ.</p> Full article ">Figure 14
<p>Schematic illustration of the Gr/a-Si PD and n-channel MOSFET (NMOSFET) connected structure. The PD is located above the NMOSFET, and the area of the PD is larger than that of the NMOSFET.</p> Full article ">Figure 15
<p>Measured Gr/a-Si PD and NMOSFET source follower output voltage under various illuminance.</p> Full article ">
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