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Materials, Volume 13, Issue 7 (April-1 2020) – 314 articles

Cover Story (view full-size image): Biophysical and biochemical cues found within the bone microenvironment were combined to form a novel biomimetic material as a strategy to address the unmet clinical need for new materials to enhance bone repair. Utilizing a collagen type I–alginate interpenetrating polymer network, a material was developed which mirrors the mechanical and structural properties of unmineralized bone, both of which have been shown to enhance osteogenesis. Moreover, by combining this material with secreted biochemical factors released by mechanically activated osteocytes, the biochemical environment of the bone niche during mechanoadaptation was further mimicked, enhancing cell viability, differentiation, and matrix deposition. View this paper.
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13 pages, 5179 KiB  
Article
Characterization of Platinum-Based Thin Films Deposited by Thermionic Vacuum Arc (TVA) Method
by Sebastian Cozma, Rodica Vlǎdoiu, Aurelia Mandes, Virginia Dinca, Gabriel Prodan and Vilma Buršíková
Materials 2020, 13(7), 1796; https://doi.org/10.3390/ma13071796 - 10 Apr 2020
Cited by 4 | Viewed by 3481
Abstract
The current work aimed to characterize the morphology, chemical, and mechanical properties of Pt and PtTi thin films deposited via thermionic vacuum arc (TVA) method on glass and silicon substrates. The deposited thin films were characterized by means of a scanning electron microscope [...] Read more.
The current work aimed to characterize the morphology, chemical, and mechanical properties of Pt and PtTi thin films deposited via thermionic vacuum arc (TVA) method on glass and silicon substrates. The deposited thin films were characterized by means of a scanning electron microscope technique (SEM). The quantitative elemental microanalysis was done using energy-dispersive X-ray spectroscopy (EDS). The tribological properties were studied by a ball-on-disc tribometer, and the mechanical properties were measured using nanoindentation tests. The roughness, as well as the micro and nanoscale features, were characterized using atomic force microscopy (AFM) and transmission electron microscopy (TEM). The wettability of the deposited Pt and PtTi thin films was investigated by the surface free energy evaluation (SFE) method. The purpose of our study was to prove the potential applications of Pt-based thin films in fields, such as nanoelectronics, fuel cells, medicine, and materials science. Full article
(This article belongs to the Special Issue Carbon-Refractory Metals Nanostructures: Synthesis, Characterization and Applications)
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Figure 1

Figure 1
<p>SEM images of: (<b>a</b>) Pt/Si and (<b>b</b>) PtTi/Si thin films deposited on Si substrate at an acceleration voltage of 15 kV and magnifications of: 1000×, and SEM images after the scratch for the determination of adhesion test: (<b>c</b>) Pt/Si and (<b>d</b>) PtTi/Si film. Images (<b>e</b>) and (<b>f</b>) present Pt/Gl and PtTi/Gl thin films deposited on a glass substrate.</p> Full article ">Figure 2
<p>Graphical elemental mapping for Pt thin film deposited on Si substrate at 1000× magnification and 15 kV acceleration voltage.</p> Full article ">Figure 3
<p>Graphical elemental mapping for PtTi thin film deposited on a glass substrate at 1000× magnification and 15 kV acceleration voltage.</p> Full article ">Figure 4
<p>Overlapped graphs of friction coefficient as a function of the distance at an applied force of 0.5 N, 1 N, and 3 N, for (<b>a</b>) Pt on a glass substrate and (<b>b</b>) PtTi on a glass substrate.</p> Full article ">Figure 5
<p>Results of the nanoindentation tests in the range of indentation loads from 0.5 to 10 mN. (<b>a</b>) Depth dependence of the hardness and (<b>b</b>) Depth dependence of the reduced elastic modulus.</p> Full article ">Figure 6
<p>Phase maps for Pt deposited on a glass substrate for areas of (<b>a</b>) 2.5 × 2.5 µm and (<b>b</b>) 1 × 1 µm.</p> Full article ">Figure 7
<p>2D (<b>a</b>) and 3D topography map (<b>b</b>) for Pt; 2D (<b>c</b>) and 3D topography image (<b>d</b>) for PtTi thin film. The studied films were deposited on a glass substrate.</p> Full article ">Figure 8
<p>Droplet images and the calculated contact angles by SEE system software using water on a glass substrate: (<b>a</b>) of Pt and (<b>b</b>) of PtTi thin films.</p> Full article ">Figure 9
<p>HRTEM images of Pt/Si (<b>a</b>) and PtTi/Si (<b>b</b>) as the sample start point for measuring the mean size of grain on this sample.</p> Full article ">Figure 10
<p>SAED (selected area electron diffraction) investigation for Pt/Si thin films: (<b>a</b>) Indexed SAED patterns of Pt/Si film. Inset shows Miller indices for FCC (Face Centered Cubic) Pt; (<b>b</b>) Electron diffraction data.</p> Full article ">Figure 11
<p>SAED investigation for PtTi/Si thin films: (<b>a</b>) Indexed SAED patterns of PtTi/Si. Inset shows Miller indices for FCC Pt tetragonal Ti α and tetragonal TiO<sub>2</sub>–anatase; (<b>b</b>) Electron diffraction data.</p> Full article ">
24 pages, 7833 KiB  
Article
An RVE-Based Study of the Effect of Martensite Banding on Damage Evolution in Dual Phase Steels
by Emin Erkan Aşık, Emin Semih Perdahcıoğlu and Ton van den Boogaard
Materials 2020, 13(7), 1795; https://doi.org/10.3390/ma13071795 - 10 Apr 2020
Cited by 14 | Viewed by 3191
Abstract
The intent of this work is to numerically investigate the effect of second phase morphology on damage evolution characteristics of dual-phase (DP) steels. A strain gradient enhanced crystal plasticity framework is used in order to capture the deformation heterogeneity caused by lattice orientations [...] Read more.
The intent of this work is to numerically investigate the effect of second phase morphology on damage evolution characteristics of dual-phase (DP) steels. A strain gradient enhanced crystal plasticity framework is used in order to capture the deformation heterogeneity caused by lattice orientations and microstructural size effects. The investigation is focused on two different martensite distributions (banded and random) that are relevant for industrial applications. The effects of martensite morphology are compared by artificially generated 2D plane strain microstructures with initial void content. The Representative volume elements (RVEs) are subjected to tensile deformation imposed by periodic boundary conditions. Evolution of voids are analyzed individually as well as a whole and characterized with respect to average axial strain. It is found that during stretching voids exhibit varying evolution characteristics due to generation of inhomogeneous strain fields within the structure. The behavior of individual voids shows that the stress-state surrounding the void is different from the imposed far field macroscopic stress-state. The voids at the ferrite martensite interface and in ferrite grains of the randomly distributed martensite grow more than in the banded structure. On the other hand, voids formed by martensite cracking growth shows an opposite trend. Full article
(This article belongs to the Section Materials Simulation and Design)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Typical microstructure of a commercial DP600 steel and distribution of vol% martensite where ND (normal direction) represents the direction normal to the plane of sheet and RD and TD represent the rolling and transverse directions of the sheet.</p> Full article ">Figure 2
<p>RVE with banded morphology, (<b>a</b>) voids (green: voids in ferrite, red: voids at the ferrite–martensite boundary) and cracks (blue), (<b>b</b>) ferrite (white) and martensite (black), (<b>c</b>) colors indicate 69 ferrite orientations, (<b>d</b>) colors indicate 29 martensite orientations.</p> Full article ">Figure 3
<p>RVE with random morphology, (<b>a</b>) voids (green: voids in ferrite, red: voids at the ferrite–martensite boundary) and cracks (blue), (<b>b</b>) ferrite (white) and martensite (black), (<b>c</b>) colors indicate 67 ferrite orientations, (<b>d</b>) colors indicate 32 martensite orientations.</p> Full article ">Figure 4
<p>RVEs used to model (<b>a</b>) ferrite, (<b>b</b>) martensite. Colors represent the Voronoi cells with different grain orientations.</p> Full article ">Figure 5
<p>Stress–strain response of DP600 (experimental), individual phases and the different morphologies.</p> Full article ">Figure 6
<p>Distribution of (<b>a</b>,<b>d</b>,<b>g</b>) <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>SSD</mi> </msub> </semantics></math> (mm<math display="inline"><semantics> <mrow> <msup> <mrow/> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>), (<b>b</b>,<b>e</b>,<b>h</b>) <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>GND</mi> </msub> </semantics></math> (mm<math display="inline"><semantics> <mrow> <msup> <mrow/> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>), (<b>c</b>,<b>f</b>,<b>i</b>) Normalized dislocation density for banded morphology. Three rows represent 3 different orientation sets.</p> Full article ">Figure 7
<p>Distribution of (<b>a</b>,<b>d</b>,<b>g</b>) <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>SSD</mi> </msub> </semantics></math> (mm<math display="inline"><semantics> <mrow> <msup> <mrow/> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>), (<b>b</b>,<b>e</b>,<b>h</b>) <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>GND</mi> </msub> </semantics></math> (mm<math display="inline"><semantics> <mrow> <msup> <mrow/> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>), (<b>c</b>,<b>f</b>,<b>i</b>) Normalized dislocation density for random morphology. Three rows represent 3 different orientation sets</p> Full article ">Figure 8
<p>Averaged statistically stored dislocation (SSD) (<b>left</b>) and geometrically necessary dislocations (GND) (<b>right</b>) densities within the RVEs. Each color represents an orientation set.</p> Full article ">Figure 9
<p>Evolution of normalized SSD density (with respect to <math display="inline"><semantics> <msubsup> <mi>ρ</mi> <mi>SSD</mi> <mn>0</mn> </msubsup> </semantics></math>) in the RVEs for ferrite (<b>left</b>) and martensite (<b>right</b>). Each color represents an orientation set.</p> Full article ">Figure 10
<p>Evolution of GND density in the RVEs for ferrite (<b>left</b>) and martensite (<b>right</b>). Each color represents an orientation set.</p> Full article ">Figure 11
<p>Evolution of total area of voids (<b>left</b>) banded, (<b>right</b>) random morphology for 3 orientation sets with total strain. Each color represents an orientation set.</p> Full article ">Figure 12
<p>Evolution of the normalized area (with respect to initial area) of individual interface voids in banded (<b>left</b>) and random (<b>right</b>) morphology with total strain. Each color represents one void.</p> Full article ">Figure 13
<p>Evolution of the normalized area of individual in-grain voids in banded (<b>left</b>) and random (<b>right</b>) morphology. Each color represents one void.</p> Full article ">Figure 14
<p>Evolution of total area of the voids formed by martensite cracks for 3 different orientation sets for random and banded distribution of martensite with total strain. Each color represents an orientation set.</p> Full article ">Figure 15
<p>Evolution of the area of individual voids formed by martensite cracking in banded (<b>left</b>) and random (<b>right</b>) morphology with total strain. Each color represents one void.</p> Full article ">
24 pages, 20194 KiB  
Article
Constitutive Models for Dynamic Strain Aging in Metals: Strain Rate and Temperature Dependences on the Flow Stress
by Yooseob Song, Daniel Garcia-Gonzalez and Alexis Rusinek
Materials 2020, 13(7), 1794; https://doi.org/10.3390/ma13071794 - 10 Apr 2020
Cited by 24 | Viewed by 4099
Abstract
A new constitutive model for Q235B structural steel is proposed, incorporating the effect of dynamic strain aging. Dynamic strain aging hugely affects the microstructural behavior of metallic compounds, in turn leading to significant alterations in their macroscopic mechanical response. Therefore, a constitutive model [...] Read more.
A new constitutive model for Q235B structural steel is proposed, incorporating the effect of dynamic strain aging. Dynamic strain aging hugely affects the microstructural behavior of metallic compounds, in turn leading to significant alterations in their macroscopic mechanical response. Therefore, a constitutive model must incorporate the effect of dynamic strain aging to accurately predict thermo-mechanical deformation processes. The proposed model assumes the overall response of the material as a combination of three contributions: athermal, thermally activated, and dynamic strain aging stress components. The dynamic strain aging is approached by two alternative mathematical expressions: (i) model I: rate-independent model; (ii) model II: rate-dependent model. The proposed model is finally used to study the mechanical response of Q235B steel for a wide range of loading conditions, from quasi-static loading ( ε ˙ = 0.001   s − 1 and ε ˙ = 0.02   s − 1 ) to dynamic loading ( ε ˙ = 800   s − 1 and ε ˙ = 7000   s − 1 ), and across a broad range of temperatures ( 93   K − 1173   K ). The results from this work highlight the importance of considering strain-rate dependences (model II) to provide reliable predictions under dynamic loading scenarios. In this regard, rate-independent approaches (model I) are rather limited to quasi-static loading. Full article
(This article belongs to the Special Issue Dynamic Behaviour of Metallic Materials)
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Figure 1

Figure 1
<p>Experimental stress-temperature graphs for Q235B steel for different strain rates (<math display="inline"><semantics> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> </semantics></math>) and strain levels: (<b>a</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> [<a href="#B1-materials-13-01794" class="html-bibr">1</a>]. Dynamic strain aging (DSA) is observed in all cases.</p> Full article ">Figure 2
<p>Dislocation density versus deformation graphs at different strain and temperature levels [<a href="#B12-materials-13-01794" class="html-bibr">12</a>,<a href="#B13-materials-13-01794" class="html-bibr">13</a>].</p> Full article ">Figure 3
<p>Profiles of model predictions (lines) and experimental data (dots) according to the temperature variation: (<b>a</b>) lower yield stress, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>U</mi> <mo>−</mo> <mi>A</mi> </mrow> </semantics></math> and (<b>c</b>) <math display="inline"><semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics></math> [<a href="#B13-materials-13-01794" class="html-bibr">13</a>].</p> Full article ">Figure 4
<p>The athermal flow stress-strain curve from the experiments [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] and the proposed model.</p> Full article ">Figure 5
<p>The thermal flow stress versus temperature curves from the experiments [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] and the VA model (Equation (15)) with (<b>a</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>The plots of <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>D</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mi>D</mi> </msub> </mrow> </semantics></math> versus <math display="inline"><semantics> <mrow> <msub> <mi>ε</mi> <mi>p</mi> </msub> </mrow> </semantics></math>. Dots for both of the parameters are obtained from the experimental data [<a href="#B1-materials-13-01794" class="html-bibr">1</a>]. The corresponding trend lines are displayed using a power law form.</p> Full article ">Figure 7
<p>The plot of <math display="inline"><semantics> <mi mathvariant="script">W</mi> </semantics></math> versus <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mi>p</mi> </msub> </mrow> </semantics></math>. Dots for both of the parameters are obtained from the experimental data [<a href="#B1-materials-13-01794" class="html-bibr">1</a>]. The corresponding trend lines are displayed using a power law form.</p> Full article ">Figure 8
<p>The DSA-induced flow stress versus temperature curves from the experiments [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] and the proposed model I with (<b>a</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>Comparisons between model predictions from the VA and proposed model I and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. Quasi-static loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 9 Cont.
<p>Comparisons between model predictions from the VA and proposed model I and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. Quasi-static loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 10
<p>Comparisons between model predictions from the VA and proposed model I and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>. and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. Quasi-static loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 11
<p>Comparisons between model predictions from the VA and proposed model I and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.05</mn> </mrow> </semantics></math> and (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>. Dynamic loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 12
<p>Comparisons between model predictions from the VA and proposed model I and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, and (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>. Dynamic loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 13
<p>The DSA-induced flow stress versus temperature curves from the experiments [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] and the proposed model II with (<b>a</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p> Full article ">Figure 14
<p>Comparisons between model predictions from the VA and proposed model II and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. Quasi-static loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 15
<p>Comparisons between model predictions from the VA and proposed model II and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. Quasi-static loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 15 Cont.
<p>Comparisons between model predictions from the VA and proposed model II and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. Quasi-static loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 16
<p>Comparisons between model predictions from the VA and proposed model II and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.05</mn> </mrow> </semantics></math> and (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>. Dynamic loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 17
<p>Comparisons between model predictions from the VA and proposed model II and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, and (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>. Dynamic loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 17 Cont.
<p>Comparisons between model predictions from the VA and proposed model II and experimental data from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>] on the total true stress versus temperature responses at (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>, and (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>. Dynamic loading with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> is applied.</p> Full article ">Figure 18
<p>Variations of the DSA peak stress with strain rate at different strain levels.</p> Full article ">Figure 19
<p>True stress-true strain curves from experimental measurement [<a href="#B1-materials-13-01794" class="html-bibr">1</a>], predictions by the VA model, proposed model (PM) I, and PM II with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>)<math display="inline"><semantics> <mrow> <mtext> </mtext> <mi>T</mi> <mo>=</mo> <mn>93</mn> <mo>,</mo> <mo> </mo> <mn>153</mn> <mo>,</mo> <mo> </mo> <mn>223</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>373</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math> (<b>b</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi>T</mi> <mo>=</mo> <mn>473</mn> <mo>,</mo> <mo> </mo> <mn>523</mn> <mo>,</mo> <mo> </mo> <mn>573</mn> <mo>,</mo> <mo> </mo> <mn>623</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>893</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math>.</p> Full article ">Figure 20
<p>True stress-true strain curves from experimental measurement [<a href="#B1-materials-13-01794" class="html-bibr">1</a>], predictions by the VA model, PM I, and PM II with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>)<math display="inline"><semantics> <mrow> <mtext> </mtext> <mi>T</mi> <mo>=</mo> <mn>93</mn> <mo>,</mo> <mo> </mo> <mn>153</mn> <mo>,</mo> <mo> </mo> <mn>289</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>373</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math> (<b>b</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi>T</mi> <mo>=</mo> <mn>473</mn> <mo>,</mo> <mo> </mo> <mn>573</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>673</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math>.</p> Full article ">Figure 21
<p>True stress-true strain curves from experimental measurement [<a href="#B1-materials-13-01794" class="html-bibr">1</a>], predictions by the VA model, PM I, and PM II with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>)<math display="inline"><semantics> <mrow> <mtext> </mtext> <mi>T</mi> <mo>=</mo> <mn>300</mn> <mo>,</mo> <mo> </mo> <mn>773</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>873</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math> (<b>b</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi>T</mi> <mo>=</mo> <mn>973</mn> <mo>,</mo> <mo> </mo> <mn>1073</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>1173</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math>.</p> Full article ">Figure 22
<p>True stress-true strain curves from experimental measurement [<a href="#B1-materials-13-01794" class="html-bibr">1</a>], predictions by the VA model, PM I, and PM II with <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>)<math display="inline"><semantics> <mrow> <mtext> </mtext> <mi>T</mi> <mo>=</mo> <mn>300</mn> <mo>,</mo> <mo> </mo> <mn>573</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>773</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math> (<b>b</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi>T</mi> <mo>=</mo> <mn>873</mn> <mo>,</mo> <mo> </mo> <mn>973</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>1073</mn> <mo> </mo> <mi>K</mi> </mrow> </semantics></math>.</p> Full article ">Figure 23
<p>PM I flow stress surfaces according to variation of temperature and strain level with (<b>a</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>. The experimental data are from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>].</p> Full article ">Figure 24
<p>The PM II flow stress surfaces according to variation of temperature and strain level with (<b>a</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>. The experimental data are from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>].</p> Full article ">Figure 24 Cont.
<p>The PM II flow stress surfaces according to variation of temperature and strain level with (<b>a</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.001</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>0.02</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>800</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>ε</mi> <mo>˙</mo> </mover> <mo>=</mo> <mn>7000</mn> <mo> </mo> <msup> <mi>s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>. The experimental data are from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>].</p> Full article ">Figure 25
<p>True stress versus strain rate graphs with three temperatures (<math display="inline"><semantics> <mrow> <mn>93</mn> <mtext> </mtext> <mi>K</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mn>473</mn> <mtext> </mtext> <mi>K</mi> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mn>873</mn> <mtext> </mtext> <mi>K</mi> </mrow> </semantics></math> ) at <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>. The experimental data are from [<a href="#B1-materials-13-01794" class="html-bibr">1</a>].</p> Full article ">
13 pages, 1847 KiB  
Article
Carvacrol Prodrugs with Antimicrobial Activity Loaded on Clay Nanocomposites
by Piera Eusepi, Lisa Marinelli, Fátima García-Villén, Ana Borrego-Sánchez, Ivana Cacciatore, Antonio Di Stefano and Cesar Viseras
Materials 2020, 13(7), 1793; https://doi.org/10.3390/ma13071793 - 10 Apr 2020
Cited by 10 | Viewed by 3119
Abstract
Background: Carvacrol, an essential oil with antimicrobial activity against a wide range of pathogens, and its water soluble carvacrol prodrugs (WSCP1-3) were intercalated into montmorillonite (VHS) interlayers to improve their stability in physiological media and promote their absorption in the intestine. Methods: Intercalation [...] Read more.
Background: Carvacrol, an essential oil with antimicrobial activity against a wide range of pathogens, and its water soluble carvacrol prodrugs (WSCP1-3) were intercalated into montmorillonite (VHS) interlayers to improve their stability in physiological media and promote their absorption in the intestine. Methods: Intercalation of prodrugs by cation exchange with montmorillonite interlayer counterions was verified by X-ray powder diffraction and confirmed by Fourier transform infrared spectroscopy and thermal analysis. Results: In vitro release studies demonstrated that montmorillonite successfully controlled the release of the adsorbed prodrugs and promoted their bioactivation only in the intestinal tract where carvacrol could develop its maximum antimicrobial activity. The amount of WSCP1, WSCP2, and WSCP3 released from VHS were 38%, 54%, and 45% at acid pH in 120 min, and 65%, 78%, and 44% at pH 6.8 in 240 min, respectively. Conclusions: The resultant hybrids successfully controlled conversion of the prodrugs to carvacrol, avoiding premature degradation of the drug. Full article
(This article belongs to the Section Advanced Composites)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>(<b>a</b>) Chemical structures of water soluble carvacrol prodrugs (WSCP1-3) and (<b>b</b>) proposed bioactivation of WSCP1-3 under alkaline conditions.</p> Full article ">Figure 2
<p>Relative difference (RD%) of prodrugs conversion over time in (<b>a</b>) water and different buffer media at pH (<b>b</b>) 1.2, (<b>c</b>) 6.8, and (<b>d</b>) 7.4. Values are the means of three experiments and error bars represent the standard deviation.</p> Full article ">Figure 3
<p>Percentage WSCP1-3 adsorption into Montmorillonite (VHS). Each experiment was repeated three times and error bars represent the standard deviation.</p> Full article ">Figure 4
<p>Nanohybrids and raw components analyzed by (<b>a</b>) X-ray Power Diffraction (XRPD), (<b>b</b>) thermogravimetric analysis (TGA), and (<b>c</b>) differential scanning calorimetry (DSC).</p> Full article ">Figure 5
<p>Nanohybrids and raw components analyzed by Fourier transform infrared (FTIR).</p> Full article ">Figure 6
<p>Amount of released WSCP1-3 at pH (<b>a</b>) 1.2 and (<b>b</b>) 6.8. Amount of carvacrol (CAR) released from WSCP1–3 and WSCP1–3 adsorbed–VHS hybrids at pH 6.8 (<b>c</b>). Each experiment was repeated three times and error bars represent the standard deviation.</p> Full article ">
13 pages, 4216 KiB  
Article
Effects of Material Nonlinearities on Design of Composite Constructions—Elasto-Plastic Behaviour
by Aleksander Muc
Materials 2020, 13(7), 1792; https://doi.org/10.3390/ma13071792 - 10 Apr 2020
Cited by 2 | Viewed by 2153
Abstract
Usually, the design of composite structures is limited to the linear elastic analysis only. The experimental results discussed in the paper demonstrate the physical non-linear behaviour both for unidirectional and woven roving composites. It is mainly connected with the micromechanical damages in composite [...] Read more.
Usually, the design of composite structures is limited to the linear elastic analysis only. The experimental results discussed in the paper demonstrate the physical non-linear behaviour both for unidirectional and woven roving composites. It is mainly connected with the micromechanical damages in composite structures, particularly with the effects of matrix cracking modeled in the form of elastic-plastic physical relations. In the present paper, the effects of both physical and geometrical non-linearities are taken into account. Their influence on the limit states (understood in the sense of buckling or failure/damage) of composite structures is discussed. The numerical examples deal with the behaviour of composite pressure vessels components, such as a cylindrical shell and the reinforcement of the junction of shells. The optimisation method of the reinforcement thickness is also formulated and solved herein. Full article
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<p>Stress/strain diagram of composites showing experimental responses. (<b>a</b>) plain woven roving—aramid/epoxy resin (Muc [<a href="#B13-materials-13-01792" class="html-bibr">13</a>]). (<b>b</b>) plain woven roving—carbon/epoxy resin (Muc [<a href="#B13-materials-13-01792" class="html-bibr">13</a>]). (<b>c</b>) plain woven roving—glass/epoxy resin (Muc [<a href="#B13-materials-13-01792" class="html-bibr">13</a>]). (<b>c</b>) plain woven roving—glass/epoxy resin (Muc [<a href="#B13-materials-13-01792" class="html-bibr">13</a>]). (<b>d</b>) unidirectional—glass/epoxy resin (Muc et al. [<a href="#B14-materials-13-01792" class="html-bibr">14</a>]). (<b>e</b>) unidirectional—glass/vinyl ester resin (the pultrusion method—Muc et al. [<a href="#B15-materials-13-01792" class="html-bibr">15</a>]).</p> Full article ">Figure 2
<p>The form of the specimens used in tensile tests PN-EN-2561-1999.</p> Full article ">Figure 3
<p>Composition of wall thicknesses of composite pressure vessels.</p> Full article ">Figure 4
<p>Loads for different variants of theoretical formulations (L/R = 5, R/t = 10, G<sub>12</sub>/E<sub>2</sub> = 0.5, ν<sub>12</sub> = 0.25)—the compressed cylindrical shell with a diaphragm.</p> Full article ">Figure 5
<p>Cross-sections of the junction. (<b>a</b>) finite element model of the pressure vessel junction. (<b>b</b>) the longitudinal cross-section. (<b>c</b>) the transverse cross-section.</p> Full article ">Figure 6
<p>Stress distributions in a direction parallel to the transverse and longitudinal planes. (<b>a</b>) elastic deformations. (<b>b</b>) comparison of elastic and elastic plastic stress distributions.</p> Full article ">Figure 7
<p>Stress distributions in a direction normal to the transverse and longitudinal planes. (<b>a</b>) elastic deformations. (<b>b</b>) comparison of elastic and elastic plastic stress distributions.</p> Full article ">Figure 8
<p>Variations of the objective functional <span class="html-italic">U</span> (the strain energy) along the nozzle opening. (<b>a</b>) initial. (<b>b</b>) final (optimal).</p> Full article ">Figure 9
<p>Schematic view of reinforcement—the longitudinal cross-section.</p> Full article ">Figure 10
<p>Distributions of the thickness reinforcement in the transverse direction.</p> Full article ">Figure 11
<p>Distributions of the thickness reinforcement in the longitudinal direction.</p> Full article ">
20 pages, 8218 KiB  
Article
Investigation on the Micro Deformation Mechanism of Asphalt Mixtures under High Temperatures Based on a Self-Developed Laboratory Test
by Jilu Li, Wei Guo, Anxin Meng, Meizhao Han and Yiqiu Tan
Materials 2020, 13(7), 1791; https://doi.org/10.3390/ma13071791 - 10 Apr 2020
Cited by 9 | Viewed by 2731
Abstract
Rutting has always been considered the main disease in asphalt pavement. Dealing with rutting disease would be benefitted by understanding the formation of rutting and testing the rutting performance of mixtures more reasonably. The objective of this paper is to systematically investigate the [...] Read more.
Rutting has always been considered the main disease in asphalt pavement. Dealing with rutting disease would be benefitted by understanding the formation of rutting and testing the rutting performance of mixtures more reasonably. The objective of this paper is to systematically investigate the rutting mechanism by employing a self-designed rutting tester along with the corresponding numerical simulations. The deformation of different positions of the existing tracking tester was found to be inconsistent, and the loading was not in line with reality. Accordingly, a more practical tester was proposed: the reduced scale circular tracking (RSCT) tester integrates the functions of asphalt mixture fabrication and rutting monitoring. The results demonstrated that the loading of the new tester is closer to the actual situation. In addition, determining the stress and displacement characteristics of particles in the asphalt mixture was found to be difficult due to the limitations of the testing methods. Therefore, a two-dimensional virtual rutting test based on the RSCT was built using PFC2D (Particle Flow Code 2 Dimension) to investigate the mechanism of formation in rutting and to obtain the corresponding guidance. The numerical simulation showed that all particles of the specimen tended to move away from the load location. The main cause of rutting formation was the eddy current flow of asphalt mastic driven by coarse aggregates. The aggregates with diameters ranging from 9.5 to 4.75 mm were observed to have the greatest contribution to rutting deformation. Therefore, the aggregate amount of these spans should be focused on in the design of mixture grading. Full article
(This article belongs to the Special Issue Asphalt Road Paving Materials)
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<p>Gradation of AC16.</p> Full article ">Figure 2
<p>Gradation of asphalt mastic.</p> Full article ">Figure 3
<p>The RSCT tester.</p> Full article ">Figure 4
<p>Deformation curve of the WTT and the RSCT test.</p> Full article ">Figure 5
<p>Dynamic creep test.</p> Full article ">Figure 6
<p>Creep curve of AC-16 asphalt mastic at 60 °C.</p> Full article ">Figure 7
<p>Establishing steps of the model.</p> Full article ">Figure 8
<p>The DEM of the virtual track test.</p> Full article ">Figure 9
<p>(<b>a</b>) Rutting deformation of the virtual track test at 110 min. (<b>b</b>) Rutting deformation of the virtual track test at 220 min. (<b>c</b>) Rutting deformation of the virtual track test at 328 min.</p> Full article ">Figure 9 Cont.
<p>(<b>a</b>) Rutting deformation of the virtual track test at 110 min. (<b>b</b>) Rutting deformation of the virtual track test at 220 min. (<b>c</b>) Rutting deformation of the virtual track test at 328 min.</p> Full article ">Figure 10
<p>Deformation curve of the virtual track test.</p> Full article ">Figure 11
<p>Coarse aggregate distribution after loading.</p> Full article ">Figure 12
<p>Displacement vector of particles.</p> Full article ">Figure 13
<p>Contact force of particles.</p> Full article ">Figure 14
<p>Contribution rate of coarse aggregates with different sizes for rutting deformation.</p> Full article ">Figure 15
<p>Total x-axis displacement of coarse aggregates.</p> Full article ">Figure 16
<p>Contribution rate of coarse aggregates of different sizes for x-axis rutting deformation.</p> Full article ">Figure 17
<p>Total y-axis displacement of coarse aggregates.</p> Full article ">Figure 18
<p>Contribution rate of coarse aggregates with different sizes for y-axis rutting deformation.</p> Full article ">
17 pages, 8708 KiB  
Article
Effect of Cast Defects on the Corrosion Behavior and Mechanism of UNS C95810 Alloy in Artificial Seawater
by Xu Zhao, Yuhong Qi, Jintao Wang, Zhanping Zhang, Jing Zhu, Linlin Quan and Dachuan He
Materials 2020, 13(7), 1790; https://doi.org/10.3390/ma13071790 - 10 Apr 2020
Cited by 9 | Viewed by 2802
Abstract
To study the effect of cast defects on the corrosion behavior and mechanism of the UNS C95810 alloy in seawater, an investigation was conducted by weight loss determination, scanning electron microscopy (SEM), confocal laser scanning microscopy (CLSM), X-ray diffraction (XRD) and electrochemical testing [...] Read more.
To study the effect of cast defects on the corrosion behavior and mechanism of the UNS C95810 alloy in seawater, an investigation was conducted by weight loss determination, scanning electron microscopy (SEM), confocal laser scanning microscopy (CLSM), X-ray diffraction (XRD) and electrochemical testing of the specimen with and without cast defects on the surface. The results show that the corrosion rate of the alloy with cast defects is higher than that of the alloy without cast defects, but the defects do not change the composition of the resulting corrosion products. The defects increase the complexity of the alloy microstructure and the tendency toward galvanic corrosion, which reduce the corrosion potential from −3.83 to −86.31 mV and increase the corrosion current density from 0.228 to 0.23 μA⋅cm−2. Full article
(This article belongs to the Special Issue Corrosion and Protection of Materials)
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<p>Weight loss of S-Cast and S-Defect immersed for different time periods in artificial seawater.</p> Full article ">Figure 2
<p>Film weight of S-Cast and S-Defect immersed for different time periods in artificial seawater.</p> Full article ">Figure 3
<p>Weight loss rate of S-Cast and S-Defect immersed for different time periods in artificial seawater.</p> Full article ">Figure 4
<p>The microstructure of S-Cast before corrosion.</p> Full article ">Figure 5
<p>Surface and point scan of S-Defect before corrosion.</p> Full article ">Figure 6
<p>The corrosion morphology of for S-Cast immersed in artificial seawater at different times: (<b>a</b>) 3 d; (<b>b</b>) local magnification at 3 d; (<b>c</b>) 10 d; (<b>d</b>) local magnification at 10d; (<b>e</b>) 30 d.</p> Full article ">Figure 6 Cont.
<p>The corrosion morphology of for S-Cast immersed in artificial seawater at different times: (<b>a</b>) 3 d; (<b>b</b>) local magnification at 3 d; (<b>c</b>) 10 d; (<b>d</b>) local magnification at 10d; (<b>e</b>) 30 d.</p> Full article ">Figure 7
<p>The corrosion morphology of for S-Defect immersed in artificial seawater at different times: (<b>a</b>) 3 d; (<b>b</b>) local magnification at 3 d; (<b>c</b>) 10 d; (<b>d</b>) local magnification at 10d; (<b>e</b>) 30 d.</p> Full article ">Figure 7 Cont.
<p>The corrosion morphology of for S-Defect immersed in artificial seawater at different times: (<b>a</b>) 3 d; (<b>b</b>) local magnification at 3 d; (<b>c</b>) 10 d; (<b>d</b>) local magnification at 10d; (<b>e</b>) 30 d.</p> Full article ">Figure 8
<p>The XRD patterns of S-Defect immersed for different time periods in artificial seawater.</p> Full article ">Figure 9
<p>The XRD patterns of (<b>a</b>) S-Cast immersed for different time periods in artificial seawater and (<b>b</b>,<b>c</b>) S-Cast partial magnification.</p> Full article ">Figure 9 Cont.
<p>The XRD patterns of (<b>a</b>) S-Cast immersed for different time periods in artificial seawater and (<b>b</b>,<b>c</b>) S-Cast partial magnification.</p> Full article ">Figure 10
<p>The polarization curve of S-Cast and S-Defect.</p> Full article ">Figure 11
<p>SEM image of S-Defect immersed in artificial seawater for 3 h.</p> Full article ">Figure 12
<p>The corrosion product film structure of S-Defect immersed in artificial seawater for a long time.</p> Full article ">Figure 13
<p>Process mechanism of corrosion behavior of S-Cast immersed in artificial seawater.</p> Full article ">Figure 14
<p>Process mechanism of corrosion behavior of S-Defect immersed in artificial seawater.</p> Full article ">
13 pages, 4566 KiB  
Article
Effect of Soda Residue Addition and Its Chemical Composition on Physical Properties and Hydration Products of Soda Residue-Activated Slag Cementitious Materials
by Yonghui Lin, Dongqiang Xu and Xianhui Zhao
Materials 2020, 13(7), 1789; https://doi.org/10.3390/ma13071789 - 10 Apr 2020
Cited by 37 | Viewed by 3339
Abstract
Soda residue (SR), the solid waste of Na2CO3 produced by ammonia soda process, pollutes water and soil, increasing environmental pressure. SR has high alkalinity, and its main components are Ca(OH)2, NaCl, CaCl2, CaSO4, and [...] Read more.
Soda residue (SR), the solid waste of Na2CO3 produced by ammonia soda process, pollutes water and soil, increasing environmental pressure. SR has high alkalinity, and its main components are Ca(OH)2, NaCl, CaCl2, CaSO4, and CaCO3, which accords with the requirements of being an alkali activator. The aim of this research is to investigate the best proportion of SR addition and the contribution of individual chemical components in SR to SR- activated ground granulated blast furnace slag (GGBS) cementitious materials. In this paper, GGBS pastes activated by SR, Ca(OH)2, Ca(OH)2 + NaCl, Ca(OH)2 + CaCl2, Ca(OH)2 + CaSO4, and Ca(OH)2 + CaCO3 were studied regarding setting time, compressive strength (1 d, 3 d, 7 d, 14 d, 28 d), hydration products, and microstructure. The results demonstrate that SR (24%)-activated GGBS pastes possess acceptable setting time and compressive strength (29.6 MPa, 28 d), and its hydration products are calcium silicate hydrate (CSH) gel, calcium aluminum silicate hydrates (CASH) gel and Friedel’s salt. CaCl2 in SR plays a main role in hydration products generation and high compressive strength of SR- activated GGBS pastes. Full article
(This article belongs to the Collection Alkali‐Activated Materials for Sustainable Construction)
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<p>Moisture content of SR (<b>a</b>) and flow chart of SR pretreatment (<b>b</b>).</p> Full article ">Figure 2
<p>XRD pattern (<b>a</b>) and SEM image (<b>b</b>) of SR.</p> Full article ">Figure 3
<p>SEM image of GGBS.</p> Full article ">Figure 4
<p>The setting time of AAS specimens: S1–S4, SR (8%, 16%, 24%, 36%)-activated GGBS pastes; S5, Ca(OH)<sub>2</sub>-activated GGBS pastes; S6, Ca(OH)<sub>2</sub> + NaCl- activated GGBS pastes; S7, Ca(OH)<sub>2</sub> + CaCl<sub>2</sub>-activated GGBS pastes; S8, Ca(OH)<sub>2</sub> + CaSO<sub>4</sub>-activated GGBS pastes; S9, and Ca(OH)<sub>2</sub> + CaCO<sub>3</sub>-activated GGBS pastes.</p> Full article ">Figure 5
<p>Compressive strength of AAS pastes: (<b>a</b>) S1–S4; (<b>b</b>) S3, S5–S9.</p> Full article ">Figure 6
<p>XRD patterns of raw GGBS and AAS pastes (S3, S5, S6, S7, S8, and S9) at 28 d.</p> Full article ">Figure 7
<p>The SEM images of (<b>a</b>) S3; (<b>b</b>) S5; (<b>c</b>) S6; (<b>d</b>) S7; (<b>e</b>) S8; (<b>f</b>) S9.</p> Full article ">Figure 8
<p>FTIR spectra of raw SR, raw GGBS, S3, S5, S7, and S8.</p> Full article ">
12 pages, 4117 KiB  
Article
Magnetic Properties of La0.9A0.1MnO3 (A: Li, Na, K) Nanopowders and Nanoceramics
by Paweł Głuchowski, Ruslan Nikonkov, Robert Tomala, Wiesław Stręk, Tatsiana Shulha, Maria Serdechnova, Mikhail Zheludkevich, Andrius Pakalaniškis, Ramūnas Skaudžius, Aivaras Kareiva, Alexander Abramov, Andrei Kholkin, Maxim V. Bushinsky and Dmitry Karpinsky
Materials 2020, 13(7), 1788; https://doi.org/10.3390/ma13071788 - 10 Apr 2020
Cited by 6 | Viewed by 3557
Abstract
Nanocrystalline La0.9A0.1MnO3 (where A is Li, Na, K) powders were synthesized by a combustion method. The powders used to prepare nanoceramics were fabricated via a high-temperature sintering method. The structure and morphology of all compounds were characterized by [...] Read more.
Nanocrystalline La0.9A0.1MnO3 (where A is Li, Na, K) powders were synthesized by a combustion method. The powders used to prepare nanoceramics were fabricated via a high-temperature sintering method. The structure and morphology of all compounds were characterized by X-ray powder diffraction (XRD) and scanning electron microscopy (SEM). It was found that the size of the crystallites depended on the type of alkali ions used. The high-pressure sintering method kept the nanosized character of the grains in the ceramics, which had a significant impact on their physical properties. Magnetization studies were performed for both powder and ceramic samples in order to check the impact of the alkali ion dopants as well as the sintering pressure on the magnetization of the compounds. It was found that, by using different dopants, it was possible to strongly change the magnetic characteristics of the manganites. Full article
(This article belongs to the Special Issue Advances in Nanostructured Materials)
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<p>XRD patterns measured for La<sub>0.9</sub>A<sub>0.1</sub>MnO<sub>3</sub> powders and ceramics.</p> Full article ">Figure 2
<p>SEM micrographs of La<sub>0.9</sub>A<sub>0.1</sub>MnO<sub>3</sub> (A: Li—<b>left</b>, Na—<b>center</b>, K—<b>right</b>) powders.</p> Full article ">Figure 3
<p>Distribution of the grain sizes in the La<sub>0.9</sub>A<sub>0.1</sub>MnO<sub>3</sub> (A: Li, Na, K) nanopowders and nanoceramics.</p> Full article ">Figure 4
<p>SEM and EDS map of La<sub>0.9</sub>K<sub>0.1</sub>MnO<sub>3</sub> powder.</p> Full article ">Figure 5
<p>SEM micrographs of La<sub>0.9</sub>A<sub>0.1</sub>MnO<sub>3</sub> (A: Li—<b>left</b>, Na—<b>center</b>, K—<b>right</b>) ceramics.</p> Full article ">Figure 6
<p>Isothermal magnetization curves measured for the initial compound LaMnO<sub>3</sub> and doped La<sub>0.9</sub>A<sub>0.1</sub>MnO<sub>3</sub> (A: Li—<b>right top</b>, Na—<b>left bottom</b>, K—<b>right bottom</b>) powder and ceramics at T = 5 K.</p> Full article ">Figure 7
<p>Field cooled and zero-field cooled dependencies of magnetization recorded for the La<sub>0.9</sub>A<sub>0.1</sub>MnO<sub>3</sub> compounds (A = Na, Li, K) and initial compound LaMnO<sub>3</sub> in a magnetic field of 1kOe.</p> Full article ">
37 pages, 6478 KiB  
Review
Towards Macroporous α-Al2O3—Routes, Possibilities and Limitations
by Simon Carstens, Ralf Meyer and Dirk Enke
Materials 2020, 13(7), 1787; https://doi.org/10.3390/ma13071787 - 10 Apr 2020
Cited by 12 | Viewed by 5756
Abstract
This article combines a systematic literature review on the fabrication of macroporous α-Al2O3 with increased specific surface area with recent results from our group. Publications claiming the fabrication of α-Al2O3 with high specific surface areas (HSSA) are [...] Read more.
This article combines a systematic literature review on the fabrication of macroporous α-Al2O3 with increased specific surface area with recent results from our group. Publications claiming the fabrication of α-Al2O3 with high specific surface areas (HSSA) are comprehensively assessed and critically reviewed. An account of all major routes towards HSSA α-Al2O3 is given, including hydrothermal methods, pore protection approaches, dopants, anodically oxidized alumina membranes, and sol-gel syntheses. Furthermore, limitations of these routes are disclosed, as thermodynamic calculations suggest that γ-Al2O3 may be the more stable alumina modification for ABET > 175 m2/g. In fact, the highest specific surface area unobjectionably reported to date for α-Al2O3 amounts to 16–24 m2/g and was attained via a sol-gel process. In a second part, we report on some of our own results, including a novel sol-gel synthesis, designated as mutual cross-hydrolysis. Besides, the Mn-assisted α-transition appears to be a promising approach for some alumina materials, whereas pore protection by carbon filling kinetically inhibits the formation of α-Al2O3 seeds. These experimental results are substantiated by attempts to theoretically calculate and predict the specific surface areas of both porous materials and nanopowders. Full article
(This article belongs to the Section Porous Materials)
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<p>Phase transformations in the alumina system according to [<a href="#B9-materials-13-01787" class="html-bibr">9</a>].</p> Full article ">Figure 2
<p>Correlation between boehmite and corundum crystallite sizes adapted from [<a href="#B11-materials-13-01787" class="html-bibr">11</a>].</p> Full article ">Figure 3
<p>Phase transformations following the boehmite path, adapted from [<a href="#B68-materials-13-01787" class="html-bibr">68</a>].</p> Full article ">Figure 4
<p>XRD pattern of sample SG-Ref0 after calcination at 1200 °C for 6 h confirms complete transformation to α-Al<sub>2</sub>O<sub>3</sub> (<span class="html-fig-inline" id="materials-13-01787-i001"> <img alt="Materials 13 01787 i001" src="/materials/materials-13-01787/article_deploy/html/images/materials-13-01787-i001.png"/></span>). All other samples display the same diffraction pattern.</p> Full article ">Figure 5
<p>Mercury instruction histograms and SEM images of the starting point syntheses SG-Ref0 (left, without polyethylene oxide [PEO]), and SG-Ref100 (right, with addition of PEO of Mm 900,000). Both samples were calcined at 1200 °C for 6 h.</p> Full article ">Figure 6
<p>SEM images of sol-gel samples reveal the influence of different additives (<b>A</b>) SG-Ref0: none, (<b>B</b>) SG-C6: adipic acid, (<b>C</b>) SG-CA34 and (<b>E</b>) SG-CA68: citric acid, (<b>D</b>) SG-C2#1 and (<b>F</b>) SG-C2#2: oxalic acid) and their respective amount on the microstructure. <span class="html-italic">φ<sub>Al</sub></span> designates the molar ratio of Al<sup>3+</sup>/additive. All samples were calcined at 1200 °C for 6 h to yield α-Al<sub>2</sub>O<sub>3</sub> (cf. <a href="#materials-13-01787-f004" class="html-fig">Figure 4</a>) [<a href="#B91-materials-13-01787" class="html-bibr">91</a>].</p> Full article ">Figure 7
<p>Superimposed mercury intrusion data of sample SG-Ref0-(80), aged at 80 °C, and calcined at 600 °C (gray), 950 °C (blue), and 1200 °C (red).</p> Full article ">Figure 8
<p>Superimposed mercury intrusion data of samples MCH-w (<b>left</b>) and MCH-o (<b>right</b>), calcined at 600 °C (gray) and 1200 °C (red), respectively. NB: For better legibility, scales are adjusted to the requirements of the data.</p> Full article ">Figure 9
<p>XRD patterns of sample MCH-w, calcined at 600 °C (gray) and 1200 °C (black), respectively. Red dotted lines indicate α-Al<sub>2</sub>O<sub>3</sub> reflexes.</p> Full article ">Figure 10
<p>Comparison of SEM images of samples MCH-w (left), MCH-o (center), and SG-Ref0-(80) (right, epoxide-mediated), all calcined at 1200 °C, illustrate the increased pore volume obtained via mutual cross-hydrolysis.</p> Full article ">Figure 11
<p>SEM images of anodized aluminum oxide (AAO) membranes having undergone different treatment: (<b>A</b>) AAO-0 pristine, (<b>B</b>) AAO-1100 after calcination at 1100 °C, and (<b>C</b>) AAO-900-Mn calcined at 900 °C after impregnation with a manganiferous solution [<a href="#B168-materials-13-01787" class="html-bibr">168</a>].</p> Full article ">Figure 12
<p>Suggested mechanism of phase transitions in the Mn-doped alumina system, adapted from [<a href="#B169-materials-13-01787" class="html-bibr">169</a>].</p> Full article ">Figure 13
<p>Automatized image analysis of SEM images (<b>A</b>) of porous AAO membranes, transformed into α-Al<sub>2</sub>O<sub>3</sub> by Mn-impregnation, with Pore Distribution Function (<b>B</b>) and Angle Distribution Function (<b>C</b>) [<a href="#B168-materials-13-01787" class="html-bibr">168</a>].</p> Full article ">Figure 14
<p>XRD patterns of AAO (<b>A</b>,<b>D</b>) and sol-gel samples (<b>B</b>,<b>C</b>) calcined at 900 °C for 6 h. Impregnation with manganiferous precursor solution yields almost pure α-Al<sub>2</sub>O<sub>3</sub> for AAO samples (<b>A</b>), with some γ-Al<sub>2</sub>O<sub>3</sub>. Mn-impregnated sol-gel material (<b>B</b>) shows only α-Al<sub>2</sub>O<sub>3</sub> reflexes, along with some hausmannite. Patterns (<b>C</b>,<b>D</b>) arise from the reference samples without impregnation. Red dotted lines indicate α-Al<sub>2</sub>O<sub>3</sub>, black dotted lines indicate γ-Al<sub>2</sub>O<sub>3</sub>, hausmannite reflexes are marked in blue.</p> Full article ">Figure 15
<p>XRD patterns of sol-gel samples calcined at 950 °C for 168 h. Sample SG-Mn-imp950-168 (<b>A</b>), impregnated with manganiferous precursor exhibits all reflexes of α-Al<sub>2</sub>O<sub>3</sub>, along with hausmannite Mn<sub>3</sub>O<sub>4</sub>, and some remaining θ-Al<sub>2</sub>O<sub>3</sub>, while the pure alumina sample SG-Ref0-950-168 (<b>C</b>) shows a pattern of a poorly crystallized θ-Al<sub>2</sub>O<sub>3</sub>. The same holds true for sample SG-Mn05-950-168 (<b>B</b>), synthesized from 95 mol-% Al- and 5 mol-% Mn-precursors. Red dotted lines indicate α-Al<sub>2</sub>O<sub>3</sub>, black dotted lines indicate θ-Al<sub>2</sub>O<sub>3,</sub> hausmannite reflexes are marked in blue.</p> Full article ">Figure 16
<p>XRD patterns of sol-gel samples calcined at 1050 °C for 12 h. The undoped reference sample SG-Ref0-1050-12 (<b>F</b>) shows a pattern of poorly crystallized θ-Al<sub>2</sub>O<sub>3</sub>. Impregnation with ferreous precursor solution (<b>E</b>) has a much weaker effect than the one observed for Mn (<b>B</b>), which contains only α-Al<sub>2</sub>O<sub>3</sub> and hausmannite Mn<sub>3</sub>O<sub>4</sub>. Much of the hausmannite can be dissolved by acid leaching, giving an XRD-pure α-Al<sub>2</sub>O<sub>3</sub> pattern (<b>A</b>). Sample SG-Mn05-1050-12 (<b>C</b>), synthesized from 95 mol-% Al- and 5 mol-% Mn-precursors, gives a similar pattern to the impregnated sampe (<b>B</b>), while incorporation of hexagonal α-Fe<sub>2</sub>O<sub>3</sub> from ferreous precursors enables a facilitated α-transition (<b>D</b>, sample SG-Fe05-1050-12), with no detectable ferreous crystal phases. Red dotted lines indicate α-Al<sub>2</sub>O<sub>3</sub> reflexes, black dotted lines indicate θ-Al<sub>2</sub>O<sub>3</sub> reflexes. Hausmannite reflexes are marked in blue.</p> Full article ">Figure 17
<p>XRD patterns of pore-protected θ-alumina samples with indicated calcination conditions and A<sub>BET</sub> determined from N<sub>2</sub> sorption measurements. The three bottom patterns arise from α-doped sol-gel alumina (α*). Red dotted lines indicate α-Al<sub>2</sub>O<sub>3</sub> reflexes, black dotted lines indicate θ-Al<sub>2</sub>O<sub>3</sub> reflexes.</p> Full article ">
15 pages, 6194 KiB  
Article
Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction
by Yu Wang and Xueyi Li
Materials 2020, 13(7), 1786; https://doi.org/10.3390/ma13071786 - 10 Apr 2020
Cited by 3 | Viewed by 2816
Abstract
Continuous monitoring for defects in oil and gas pipelines is important for leakage prevention. This paper proposes a new kind of pipe elbow damage identification technique, which consists of three processes. First, piezoelectric sensors evenly arranged along the circumference of the pipeline in [...] Read more.
Continuous monitoring for defects in oil and gas pipelines is important for leakage prevention. This paper proposes a new kind of pipe elbow damage identification technique, which consists of three processes. First, piezoelectric sensors evenly arranged along the circumference of the pipeline in the turn generated ultrasonic guided wave signals in the elbow. Then, the wavefront flight time at each grid node in the known sound field were computed using the fast-marching algorithm. Finally, an elbow wall thickness map reconstruction technique based on the sparse inversion method was proposed to identify elbow defects. Compared with the traditional elbow defect identification technology, this technology can not only detect the existence of the defect but also accurately locate the defect position. Full article
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<p>Coordinate system used to simplify forward model.</p> Full article ">Figure 2
<p>Ultrasonic guided wave propagation path in different coordinate systems of (<b>a</b>) the 3-D surface of elbow and (<b>b</b>) the 2-D mapped surface.</p> Full article ">Figure 3
<p>Sound field model analyses: (<b>a</b>) non-uniformity analysis and (<b>b</b>) anisotropic analysis.</p> Full article ">Figure 4
<p>The point distribution for the calculation of the guided wave flight time. At most eight points of travel time information is required in second-order difference form.</p> Full article ">Figure 5
<p>The setting of sound field threshold. Based on the dispersion curve, it can be deduced that the guided wave velocity boundary is 5068 corresponding to the defect recognition resolution of 0.1 mm.</p> Full article ">Figure 6
<p>The flowchart of sparse inversion image reconstruction.</p> Full article ">Figure 7
<p>(<b>a</b>) Initial sound field model; (<b>b</b>) reconstruction results with the sound field threshold set as 0, which means non-sparse inversion method was used; and (<b>c</b>) reconstruction results with the sound field threshold set as 100.</p> Full article ">Figure 8
<p>The diagram of ultrasonic guided wave detection scheme.</p> Full article ">Figure 9
<p>Ultrasonic guided wave detection experimental platform.</p> Full article ">Figure 10
<p>Cross-hole scanning structure.</p> Full article ">Figure 11
<p>The monitoring signal excited at sensor E9.</p> Full article ">Figure 12
<p>Process defect for elbow.</p> Full article ">Figure 13
<p>Quantitative curve of defect.</p> Full article ">Figure 14
<p>Image reconstruction results of elbow with defect in extrados: (<b>a</b>) Reconstruction results of wall thickness map; and (<b>b</b>) identification results of the defect size.</p> Full article ">Figure 15
<p>Inversion algorithm calculation process.</p> Full article ">
14 pages, 3049 KiB  
Article
Dynamic Adsorption of Sulfamethoxazole from Aqueous Solution by Lignite Activated Coke
by Haiyan Li, Juan He, Kaiyu Chen, Zhou Shi, Mengnan Li, Pengpeng Guo and Liyuan Wu
Materials 2020, 13(7), 1785; https://doi.org/10.3390/ma13071785 - 10 Apr 2020
Cited by 14 | Viewed by 3024
Abstract
In this paper, lignite activated coke was used as adsorbent for dynamic column adsorption experiments to remove sulfamethoxazole from aqueous solution. The effects of column height, flow rate, initial concentration, pH and humic acids concentration on the dynamic adsorption penetration curve and mass [...] Read more.
In this paper, lignite activated coke was used as adsorbent for dynamic column adsorption experiments to remove sulfamethoxazole from aqueous solution. The effects of column height, flow rate, initial concentration, pH and humic acids concentration on the dynamic adsorption penetration curve and mass transfer zone length were investigated. Results showed penetration time would be prolonged significantly by increasing column height, while inhibited by the increasement of initial concentration and flow rate. Thomas and Yoon-Nelson model and the Adams-Bohart model were used to elucidate the adsorption mechanism, high coefficients of R2 > 0.95 were obtained in Thomas model for most of the adsorption entries, which revealed that the adsorption rate could probably be dominated by mass transfer at the interface. The average change rates of mass transfer zone length to the changes of each parameters, such as initial concentration, the column height, the flow rate and pH, were 0.0003, 0.6474, 0.0076, 0.0073 and 0.0191 respectively, revealed that column height may play a vital role in dynamic column adsorption efficiency. These findings suggested that lignite activated coke can effectively remove sulfamethoxazole contaminants from wastewater in practice. Full article
(This article belongs to the Special Issue Advanced Carbon Materials in Water Treatment or Separations Technology)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The experimental device of column adsorption.</p> Full article ">Figure 2
<p>(<b>a</b>) The effect of different concentration of sulfamethoxazole adsorption breakthrough curves; (<b>b</b>) Partially enlarged screening from 0 to 1600 bed volume. Experiment condition: flow rate of 3 mL/min, column height of 3 cm, pH 6.5, sulfamethoxazole concentration of 35 and 70 mg/L, respectively.</p> Full article ">Figure 3
<p>The adsorption effect of different column height on breakthrough curves, Experiment condition: sulfamethoxazole concentration of 35 mg/L, flow rate of 3 mL/min, pH 6.5, column height 3, 7 cm, respectively.</p> Full article ">Figure 4
<p>(<b>a</b>) The adsorption effect of different flow rate on breakthrough curves; (<b>b</b>) Partially enlarged screening from 0 to 1600 bed volume. Experiment condition: sulfamethoxazole concentration of 35 mg/L, pH 6.5, column height of 3 cm, flow rate of 3, 5 mL/min, respectively.</p> Full article ">Figure 5
<p>(<b>a</b>) The adsorption effect of different pH on breakthrough curves, (<b>b</b>) Partially enlarged screening from 0 to 1600 bed volume. Experiment condition: flow rate of 3 mL/min, column height of 3 cm, sulfamethoxazole concentration of 35 mg/L, pH 4, 6.5, 8 respectively.</p> Full article ">Figure 6
<p>(<b>a</b>) The adsorption effect of different concentration of human acids on breakthrough curves, (<b>b</b>) Partially enlarged screening from 0 to 1600 bed volume. Experiment condition: flow rate of 3 mL/min, column height of 3 cm, sulfamethoxazole concentration of 35 mg/L, pH 6.5, humic acids concentration= 0, 0.1, 1, 10 mg/L, respectively.</p> Full article ">Figure 7
<p>Adsorption breakthrough curves fitted by different models with sulfamethoxazole initial concentration of 35 mg/L, flow rate of 3 mL/min, pH 6.5, column height of 3 cm.</p> Full article ">Figure 8
<p>The homogeneous surface diffusion model (HDSM) diffusion model fitted breakthrough curve Experiment condition: sulfamethoxazole concentration of 35 mg/L, flow rate of 3 mL/min, pH 6.5, column height 3 cm.</p> Full article ">
17 pages, 3300 KiB  
Article
Acetic Acid and Ammonium Persulfate Pre-Treated Copper Foil for the Improvement of Graphene Quality, Sensitivity and Specificity of Hall Effect Label-Free DNA Hybridization Detection
by Naiyuan Cui, Fei Wang and Hanyuan Ding
Materials 2020, 13(7), 1784; https://doi.org/10.3390/ma13071784 - 10 Apr 2020
Cited by 2 | Viewed by 3875
Abstract
The capability of graphene-based biosensors used to detect biomolecules, such as DNA and cancer marker, is enormously affected by the quality of graphene. In this work, high quality and cleanness graphene were obtained by CVD based on acetic acid (AA) and ammonium persulfate [...] Read more.
The capability of graphene-based biosensors used to detect biomolecules, such as DNA and cancer marker, is enormously affected by the quality of graphene. In this work, high quality and cleanness graphene were obtained by CVD based on acetic acid (AA) and ammonium persulfate (AP) pretreated copper foil substrate. Hall effect devices were made by three kinds of graphene which were fabricated by CVD using no-treated copper foil, AA pre-treated copper foil and AP pre-treated copper foil. Hall effect devices made of AA pre-treated copper foil CVD graphene and AP pre-treated copper foil CVD graphene can both enhance the sensitivity of graphene-based biosensors for DNA recognition, but the AA pre-treated copper foil CVD graphene improves more (≈4 times). This may be related to the secondary oxidation of AP pre-treated copper foil in the air due to the strong corrosion of ammonium persulfate, which leads to the quality decrease of graphene comparing to acetic acid. Our research provides an efficient method to improve the sensitivity of graphene-based biosensors for DNA recognition and investigates an effect of copper foil oxidation on the growth graphene. Full article
(This article belongs to the Special Issue Carbon Nanomaterials for Imaging and Sensing)
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<p>(<b>a</b>) Graphene transfer process; (<b>b</b>) Hall effect device fabrication process; (<b>c</b>) DNA hybridization on graphene.</p> Full article ">Figure 2
<p>SEM of (<b>a</b>) pristine copper foil without pre-treatment; (<b>b</b>) copper foil treated with AP solution; (<b>c</b>) copper foil treated with AA solution; (<b>d</b>) graphene grown on pristine copper foil without pre-treatment; (<b>e</b>) graphene grown on copper foil treated with AP solution; (<b>f</b>) graphene grown on copper foil treated with AA solution.</p> Full article ">Figure 3
<p>Surface etching process of copper foils by (<b>a</b>) AP; (<b>b</b>) AA.</p> Full article ">Figure 4
<p>The AFM of (<b>a</b>) and (<b>d</b>) graphene grown on pristine copper foil; (<b>b</b>) and (<b>e</b>) graphene grown on copper foil pre-treated by AP; (<b>c</b>) and (<b>f</b>) graphene grown on copper foil pre-treated by AA; (<b>g</b>) and (<b>j</b>) pristine copper foil; (<b>h</b>) and (<b>k</b>) copper foil pre-treated by AP; (<b>i</b>) and (<b>l</b>) copper foil pre-treated by AA.</p> Full article ">Figure 5
<p>Raman shift of the three kind of graphene on SiO<sub>2</sub>/Si substrate.</p> Full article ">Figure 6
<p>XPS of (<b>a</b>) graphene grown on copper foil pre-treated by AA; (<b>b</b>) graphene grown on copper foil pre-treated by AP; (<b>c</b>) graphene grown on pristine copper foil.</p> Full article ">Figure 7
<p>Electrical performances of the three kind of graphene: (<b>a</b>) carrier concentration; (<b>b</b>) sheet resistance; (<b>c</b>) mobility.</p> Full article ">Figure 8
<p>Electrical performance of graphene modified by probe DNA: (<b>a</b>) mobility; (<b>b</b>) carrier concentration.</p> Full article ">Figure 9
<p>The electrical performance of three kinds graphene-based biosensors for the detection of target DNA: (<b>a</b>) carrier concentration; (<b>b</b>) mobility; (<b>c</b>) sheet resistance.</p> Full article ">Figure 10
<p>The variation of (<b>a</b>) carrier concentration; (<b>b</b>) carrier mobility and (<b>c</b>) sheet resistance of graphene-based Hall effect devices as a function of added concentrations of target and one-base mismatched DNA, respectively, based on AA graphene; (<b>d</b>) structure of electric double layer.</p> Full article ">Figure 11
<p>(<b>a</b>) The variation of carrier concentration of three kinds of graphene-based Hall effect devices as a function of added concentrations of target DNA; (<b>b</b>) the mechanism of higher sensitivity based on graphene with cleaner surface.</p> Full article ">
10 pages, 1429 KiB  
Article
Comparison of the Primary Stability of Porous Tantalum and Titanium Acetabular Revision Constructs
by Nicholas A. Beckmann, Rudi G. Bitsch, Mareike Schonhoff, Klaus-Arno Siebenrock, Martin Schwarze and Sebastian Jaeger
Materials 2020, 13(7), 1783; https://doi.org/10.3390/ma13071783 - 10 Apr 2020
Cited by 12 | Viewed by 5129
Abstract
Adequate primary stability of the acetabular revision construct is necessary for long-term implant survival. The difference in primary stability between tantalum and titanium components is unclear. Six composite hemipelvises with an acetabular defect were implanted with a tantalum augment and cup, using cement [...] Read more.
Adequate primary stability of the acetabular revision construct is necessary for long-term implant survival. The difference in primary stability between tantalum and titanium components is unclear. Six composite hemipelvises with an acetabular defect were implanted with a tantalum augment and cup, using cement fixation between cup and augment. Relative motion was measured at cup/bone, cup/augment and bone/augment interfaces at three load levels; the results were compared to the relative motion measured at the same interfaces of a titanium cup/augment construct of identical dimensions, also implanted into composite bone. The implants showed little relative motion at all load levels between the augment and cup. At the bone/augment and bone/cup interfaces the titanium implants showed less relative motion than tantalum at 30% load (p < 0.001), but more relative motion at 50% (p = n.s.) and 100% (p < 0001) load. The load did not have a significant effect at the augment/cup interface (p = 0.086); it did have a significant effect on relative motion of both implant materials at bone/cup and bone/augment interfaces (p < 0.001). All interfaces of both constructs displayed relative motion that should permit osseointegration. Tantalum, however, may provide a greater degree of primary stability at higher loads than titanium. The clinical implication is yet to be seen Full article
(This article belongs to the Special Issue Novel Research about Biomechanics and Biomaterials Used in Hip, Knee and Related Joints)
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<p>Photograph of titanium Gription cup and augment (<b>left</b>) and tantalum Trabecular Metal augment and cup (<b>right</b>) after implant explantation, demontrating the differences in their hole positions and augment geometry.</p> Full article ">Figure 2
<p>Schematic graph displaying the load applied for each sample over the 3000 test cycles.</p> Full article ">Figure 3
<p>Graph displaying the average relative motion (µm) at the tantalum and titanium augment and cup interfaces at the three tested load levels (30%, 50% and 100% load).</p> Full article ">Figure 4
<p>Graph shows the average relative motion (µm) between the tantalum and titanium augment and adjacent composite bone at the three tested load levels (30%, 50% and 100% load).</p> Full article ">Figure 5
<p>Graph showing the average relative motion (µm) between the tantalum and titanium cup and composite bone at the three tested load levels (30%, 50% and 100% load).</p> Full article ">
8 pages, 1426 KiB  
Communication
An Investigation on the Electrochemical Behavior and Antibacterial and Cytotoxic Activity of Nickel Trithiocyanurate Complexes
by Amir M. Ashrafi, Pavel Kopel and Lukas Richtera
Materials 2020, 13(7), 1782; https://doi.org/10.3390/ma13071782 - 10 Apr 2020
Cited by 5 | Viewed by 2700
Abstract
The electrochemical redox behavior of three trinuclear Ni(II) complexes [Ni3(abb)3(H2O)3(µ-ttc)](ClO4)3 (1), [Ni3(tebb)3(H2O)3(µ-ttc)](ClO4)3·H2O (2), and [...] Read more.
The electrochemical redox behavior of three trinuclear Ni(II) complexes [Ni3(abb)3(H2O)3(µ-ttc)](ClO4)3 (1), [Ni3(tebb)3(H2O)3(µ-ttc)](ClO4)3·H2O (2), and [Ni3(pmdien)3(µ-ttc)](ClO4)3 (3), where abb = 1-(1H-benzimidazol-2-yl)-N-(1H-benzimidazol-2-ylmethyl)methan-amine, ttcH3 = trithiocyanuric acid, tebb = 2-[2-[2-(1H-benzimidazol-2-yl)ethylsulfanyl]ethyl]-1H-benzimidazole, and pmdien = N,N,N′,N″,N″-pentamethyldiethylenetriamine is reported. Cyclic voltammetry (CV) was applied for the study of the electrochemical behavior of these compounds. The results confirmed the presence of ttc and nickel in oxidation state +2 in the synthesized complexes. Moreover, the antibacterial properties and cytotoxic activity of complex 3 was investigated. All the complexes show antibacterial activity against Staphylococcus aureus and Escherichia coli to different extents. The cytotoxic activity of complex 3 and ttcNa3 were studied on G-361, HOS, K-562, and MCF7 cancer cell lines. It was found out that complex 3 possesses the cytotoxic activity against the tested cell lines, whereas ttcNa3 did not show any cytotoxic activity. Full article
(This article belongs to the Special Issue Synthesis, Characterization and Applications of Metal Complexes)
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Figure 1
<p>(<b>A</b>) Cyclic voltammogram of <b>a</b>: Blank (buffer composed of 1.750 mL H<sub>2</sub>O + 100 μL of the mixture (1 M HCl + 3 M NH<sub>3</sub>)), <b>b</b>: Ni<sup>2+</sup> 250 ppb, <b>c</b>: ttc 5 × 10<sup>−4</sup> M, (<b>B</b>) CV of (<b>1</b>), 5 × 10<sup>−4</sup> M, (<b>C</b>) CV of (<b>2</b>), (<b>D</b>) CV of (<b>3</b>), 5 × 10<sup>−4</sup> M. CV parameters: start potential −1.5 V, final potential 0.0 V, scan rate 50 mV·s<sup>−1</sup>.</p> Full article ">Figure 2
<p>Testing of antimicrobial activity of complex <b>3</b> in concentration range 0.002–0.500 mg·mL<sup>−1</sup> after 21 h of treatment on <span class="html-italic">S. aureus</span>, <span class="html-italic">E. coli,</span> and <span class="html-italic">MRSA</span>.</p> Full article ">Scheme 1
<p>Trinuclear nickel(II) cations depicted with Mercury software [<a href="#B29-materials-13-01782" class="html-bibr">29</a>]. Green stands for nickel, violet for nitrogen, yellow for sulfur, and red for oxygen atoms. Perchlorate anions and hydrogen atoms were omitted for clarity. The structural data of the complexes can be found in [<a href="#B26-materials-13-01782" class="html-bibr">26</a>,<a href="#B27-materials-13-01782" class="html-bibr">27</a>,<a href="#B28-materials-13-01782" class="html-bibr">28</a>]. The ligands abb = 1-(1H-benzimidazol-2-yl)-N-(1H-benzimidazol-2-ylmethyl)methan-amine, tebb = 2-[2-[2-(1H-benzimidazol-2-yl)ethylsulfanyl]ethyl]-1H-benzimidazole, and pmdien = N,N,N′,N″,N″-pentamethyldiethylenetriamine are depicted under corresponding complexes.</p> Full article ">Scheme 2
<p>The proposed electrochemical redox mechanism of ttc. (<b>A</b>): two pathways of oxidation of ttc, (<b>B</b>): oxidation of ttc followed by the polymerization.</p> Full article ">
22 pages, 20425 KiB  
Article
Effects of Chemically Treated Eucalyptus Fibers on Mechanical, Thermal and Insulating Properties of Polyurethane Composite Foams
by Sylwia Członka, Anna Strąkowska, Piotr Pospiech and Krzysztof Strzelec
Materials 2020, 13(7), 1781; https://doi.org/10.3390/ma13071781 - 10 Apr 2020
Cited by 43 | Viewed by 4081
Abstract
In this work, rigid polyurethane (PUR) foams were prepared by incorporating 2 wt% of eucalyptus fibers. The eucalyptus fibers were surface-modified by maleic anhydride, alkali, and silane (triphenylsilanol) treatment. The impact of the modified eucalyptus fibers on the mechanical, thermal, and fire performances [...] Read more.
In this work, rigid polyurethane (PUR) foams were prepared by incorporating 2 wt% of eucalyptus fibers. The eucalyptus fibers were surface-modified by maleic anhydride, alkali, and silane (triphenylsilanol) treatment. The impact of the modified eucalyptus fibers on the mechanical, thermal, and fire performances of polyurethane foams was analyzed. It was observed that the addition of eucalyptus fibers showed improved mechanical and thermal properties and the best properties were shown by silane-treated fibers with a compressive strength of 312 kPa and a flexural strength of 432 kPa. Moreover, the thermal stability values showed the lowest decline for polyurethane foams modified with the silane-treated fibers, due to the better thermal stability of such modified fibers. Furthermore, the flame resistance of polyurethane foams modified with the silane-treated fibers was also the best among the studied composites. A cone calorimetry test showed a decrease in the peak of heat release from 245 to 110 kW∙m−2 by the incorporation of silane-treated fibers. Furthermore, total heat release and total smoke release were also found to decrease remarkably upon the incorporation of silane-treated fibers. The value of limiting oxygen index was increased from 20.2% to 22.1%. Char residue was also found to be increased from 24.4% to 28.3%. It can be concluded that the application of chemically modified eucalyptus fibers has great potential as an additive to incorporate good mechanical, thermal, and fire properties in rigid polyurethane foams. Full article
(This article belongs to the Special Issue Development of Bio-Based Composite Foams)
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<p>Alkali treatment of eucalyptus fibers.</p> Full article ">Figure 2
<p>Silane treatment of eucalyptus fibers.</p> Full article ">Figure 3
<p>Maleic anhydride treatment of eucalyptus fibers.</p> Full article ">Figure 4
<p>Schematic representation for the preparation of polyurethane foams modified with eucalyptus fibers.</p> Full article ">Figure 5
<p>The viscosity of the polyol system modified with eucalyptus fibers in the function of the shear rate.</p> Full article ">Figure 6
<p>Fourier-transform Infrared Spectroscopy (FTIR) spectra of chemically-treated eucalyptus fibers.</p> Full article ">Figure 7
<p>Optical image of (<b>a</b>) EF_NT, (<b>b</b>) EF_A, (<b>c</b>) EF_M and (<b>d</b>) EF_S observed at a magnification of 200.</p> Full article ">Figure 8
<p>(<b>a</b>) thermogravimetric analysis curve (TGA) and (<b>b</b>) first derivative of the TGA curve (DTG) obtained for polyurethane foams modified with eucalyptus fibers.</p> Full article ">Figure 9
<p>The possible mechanism between (<b>a</b>) alkali-treated, (<b>b</b>) silane-treated, (<b>c</b>) maleic-treated eucalyptus fibers and isocyanate groups.</p> Full article ">Figure 10
<p>The morphology of (<b>a</b>) F_EF_0, (<b>b</b>) F_EF_NT, (<b>c</b>) F_EF_A, (<b>d</b>) F_EF_M, (<b>e</b>) F_EF_S observed at a magnification of ×100.</p> Full article ">Figure 11
<p>The morphology of (<b>a</b>) F_EF_0, (<b>b</b>) F_EF_NT, (<b>c</b>) F_EF_A, (<b>d</b>) F_EF_M, (<b>e</b>) F_EF_S observed at a magnification of ×200.</p> Full article ">Figure 12
<p>Water uptake of polyurethane (PUR) foams.</p> Full article ">Figure 13
<p>The contact angle of (<b>a</b>) F_EF_0, (<b>b</b>) F_EF_NT, (<b>c</b>) F_EF_A, (<b>d</b>) F_EF_M, (<b>e</b>) F_EF_S.</p> Full article ">Figure 14
<p>(<b>a</b>) TG and (<b>b</b>) DTG curves obtained for polyurethane foams modified with eucalyptus fibers.</p> Full article ">Figure 15
<p>(<b>a</b>) peak heat release rate (pHRR) and (<b>b</b>) total smoke release (TSR) values obtained for polyurethane foams modified with eucalyptus fibers.</p> Full article ">
16 pages, 4861 KiB  
Article
Comparative Study on Flow-Accelerated Corrosion and Erosion–Corrosion at a 90° Carbon Steel Bend
by Li Zeng, Geng Chen and Hanxin Chen
Materials 2020, 13(7), 1780; https://doi.org/10.3390/ma13071780 - 10 Apr 2020
Cited by 52 | Viewed by 6172
Abstract
Electrochemical measurements and surface analysis are performed to comparatively study flow-accelerated corrosion (FAC) and erosion–corrosion (E-C) behavior at a 90° carbon steel bend. The corrosion rates are higher under FAC conditions than those under E-C conditions. For FAC, the corrosion is more serious [...] Read more.
Electrochemical measurements and surface analysis are performed to comparatively study flow-accelerated corrosion (FAC) and erosion–corrosion (E-C) behavior at a 90° carbon steel bend. The corrosion rates are higher under FAC conditions than those under E-C conditions. For FAC, the corrosion is more serious at the inside wall. However, corrosion is exacerbated at the outside wall under E-C conditions. No erosion scratches are observed under FAC conditions and at the inside wall under E-C conditions, while remarkable erosion scratches appear at the outside wall under E-C conditions. The dominant hydrodynamics affecting FAC and E-C are remarkably different. Full article
(This article belongs to the Section Corrosion)
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<p>Schematic diagrams of the loop apparatus and bend testing zone for flowing tests: (<b>a</b>) loop apparatus; (<b>b</b>) bend testing zone; (<b>c</b>) array electrodes distribution at the outside wall; (<b>d</b>) array electrodes distribution at the inside wall.</p> Full article ">Figure 2
<p>(<b>a</b>) Distribution of the total erosion–corrosion (E-C) rate after the E-C test; (<b>b</b>) contours of the total E-C rate after the E-C test; (<b>c</b>) distribution of the total corrosion rate after the E-C test; (<b>d</b>) contours of the total corrosion rate after the E-C test.</p> Full article ">Figure 2 Cont.
<p>(<b>a</b>) Distribution of the total erosion–corrosion (E-C) rate after the E-C test; (<b>b</b>) contours of the total E-C rate after the E-C test; (<b>c</b>) distribution of the total corrosion rate after the E-C test; (<b>d</b>) contours of the total corrosion rate after the E-C test.</p> Full article ">Figure 3
<p>(<b>a</b>) Distribution of corrosion rate after the flow-accelerated corrosion (FAC) test and (<b>b</b>) contours of corrosion rate after FAC test.</p> Full article ">Figure 4
<p>Nyquist plots under FAC and E-C conditions.</p> Full article ">Figure 5
<p>Nyquist (<b>a</b>) and Bode (<b>b</b>) plots of electrodes under the static state.</p> Full article ">Figure 6
<p>Electrochemical equivalent circuits: (<b>a</b>) under flow conditions; (<b>b</b>) under static-state conditions.</p> Full article ">Figure 7
<p>Potentiodynamic polarization curves under flow and static conditions.</p> Full article ">Figure 8
<p>SEM surface morphologies of electrodes under flow and static conditions: (<b>a</b>) electrode 6 (outside), FAC test; (<b>b</b>) electrode 14 (inside), FAC test; (<b>c</b>) electrode 6 (outside), E-C test; (<b>d</b>) electrode 14 (inside), E-C test; (<b>e</b>) under static-state conditions.</p> Full article ">Figure 9
<p>Schematic of the electrodes in different positions of the bend under flow conditions: (<b>a</b>) under FAC conditions; (<b>b</b>) under E-C conditions.</p> Full article ">
10 pages, 2656 KiB  
Article
C-S-H Pore Size Characterization Via a Combined Nuclear Magnetic Resonance (NMR)–Scanning Electron Microscopy (SEM) Surface Relaxivity Calibration
by Christoph Naber, Florian Kleiner, Franz Becker, Long Nguyen-Tuan, Christiane Rößler, Merlin A. Etzold and Jürgen Neubauer
Materials 2020, 13(7), 1779; https://doi.org/10.3390/ma13071779 - 10 Apr 2020
Cited by 22 | Viewed by 3393
Abstract
A new method for the nuclear magnetic resonance (NMR) surface relaxivity calibration in hydrated cement samples is proposed. This method relies on a combined analysis of 28-d hydrated tricalcium silicate samples by scanning electron microscopy (SEM) image analysis and 1H-time-domain (TD)-NMR relaxometry. [...] Read more.
A new method for the nuclear magnetic resonance (NMR) surface relaxivity calibration in hydrated cement samples is proposed. This method relies on a combined analysis of 28-d hydrated tricalcium silicate samples by scanning electron microscopy (SEM) image analysis and 1H-time-domain (TD)-NMR relaxometry. Pore surface and volume data for interhydrate pores are obtained from high resolution SEM images on surfaces obtained by argon broad ion beam sectioning. These data are combined with T2 relaxation times from 1H-TD-NMR to calculate the systems surface relaxivity according to the fast exchange model of relaxation. This new method is compared to an alternative method that employs sequential drying to calibrate the systems surface relaxivity. Full article
(This article belongs to the Section Construction and Building Materials)
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<p>Solid-echo decay of a 28d hydrated C<sub>3</sub>S sample (black circles) with the Gaussian and exponential decay fits.</p> Full article ">Figure 2
<p>CPMG decay of a 28-d hydrated C<sub>3</sub>S sample (black circles) with the multiexponential fitting results using four exponential decay functions.</p> Full article ">Figure 3
<p>Two exemplary image segmentation results. The acquired SEM images (<b>a,c</b>) and the resulting segmentation with the pores in green (<b>b,d</b>). All images have the same scale bar.</p> Full article ">Figure 4
<p>Interhydrate pore size distribution from automated image analysis of Ar-BIB milled 28 d hydrated C<sub>3</sub>S samples. The chord-length density function (CDF) was determined as pore diameter.</p> Full article ">
27 pages, 3525 KiB  
Article
On the Microstructure and Properties of Nb-12Ti-18Si-6Ta-2.5W-1Hf (at.%) Silicide-Based Alloys with Ge and Sn Additions
by Jiang Zhao, Claire Utton and Panos Tsakiropoulos
Materials 2020, 13(7), 1778; https://doi.org/10.3390/ma13071778 - 10 Apr 2020
Cited by 18 | Viewed by 2981
Abstract
In this paper two Nb-silicide-based alloys with nominal compositions (at.%) Nb-12Ti-18Si-6Ta-2.5W-1Hf-2Sn-2Ge (JZ1) and Nb-12Ti-18Si-6Ta-2.5W-1Hf-5Sn-5Ge (JZ2) were studied. The alloys were designed using the alloy design methodology NICE to meet specific research objectives. The cast microstructures of both alloys were sensitive to solidification conditions. [...] Read more.
In this paper two Nb-silicide-based alloys with nominal compositions (at.%) Nb-12Ti-18Si-6Ta-2.5W-1Hf-2Sn-2Ge (JZ1) and Nb-12Ti-18Si-6Ta-2.5W-1Hf-5Sn-5Ge (JZ2) were studied. The alloys were designed using the alloy design methodology NICE to meet specific research objectives. The cast microstructures of both alloys were sensitive to solidification conditions. There was macro-segregation of Si in JZ1 and JZ2. In both alloys the βNb5Si3 was the primary phase and the Nbss was stable. The A15-Nb3X (X = Ge,Si,Sn) was stable only in JZ2. The Nbss+βNb5Si3 eutectic in both alloys was not stable as was the Nb3Si silicide that formed only in JZ1. At 800 °C both alloys followed linear oxidation kinetics and were vulnerable to pesting. At 1200 °C both alloys exhibited parabolic oxidation kinetics in the early stages and linear kinetics at longer times. The adhesion of the scale that formed on JZ2 at 1200 °C and consisted of Nb and Ti-rich oxides, silica and HfO2 was better than that of JZ1. The microstructure of JZ2 was contaminated by oxygen to a depth of about 200 μm. There was no Ge or Sn present in the scale. The substrate below the scale was richer in Ge and Sn where the NbGe2, Nb5(Si1-xGex)3, W-rich Nb5(Si1-xGex)3, and A15-Nb3X compounds (X = Ge,Si,Sn) were formed in JZ2. The better oxidation behavior of JZ2 compared with JZ1 correlated well with the decrease in VEC and increase in δ parameter values, in agreement with NICE. For both alloys the experimental data for Si macrosegregation, vol.% Nbss, chemical composition of Nbss and Nb5Si3, and weight gains at 800 and 1200 °C was compared with the calculations (predictions) of NICE. The agreement was very good. The calculated creep rates of both alloys at 1200 °C and 170 MPa were lower than that of the Ni-based superalloy CMSX-4 for the same conditions but higher than 10−7 s−1. Full article
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<p>X-ray diffractograms of the (<b>a</b>) as-cast and (<b>b</b>) heat-treated alloy JZ1.</p> Full article ">Figure 2
<p>Backscattered electron (BSE) images of the microstructure of JZ1-AC in the (<b>a</b>) top and (<b>c</b>) bottom (<b>b</b>) showing the transition from the bulk to the bottom. (<b>d</b>) to (<b>f</b>) show the details of the microstructure in the bottom of the button of JZ1-AC where the Nb<sub>3</sub>Si silicide was observed.</p> Full article ">Figure 3
<p>BSE images of the microstructures of the heat-treated alloys (<b>a</b>) JZ1 and (<b>b</b>) JZ2.</p> Full article ">Figure 4
<p>X-ray diffractograms of the (<b>a</b>) as-cast and (<b>b</b>) heat-treated alloy JZ2.</p> Full article ">Figure 5
<p>BSE images of the microstructure of JZ2-AC in (<b>a</b>) bulk, (<b>b</b>) and (<b>c</b>) the transition from the bottom to the bulk and (<b>d</b>) bottom of the button. (<b>c</b>) Corresponds to the area shown by square in (<b>b</b>).</p> Full article ">Figure 6
<p>Thermogravimetric (TG) data for the alloys JZ1 (<b>a</b>,<b>c</b>) and JZ2 (<b>b</b>,<b>d</b>) for 800 °C (<b>a</b>,<b>b</b>) and 1200 °C (<b>c</b>,<b>d</b>).</p> Full article ">Figure 7
<p>The specimens of the alloys JZ1 (<b>a</b>,<b>c</b>) and JZ2 (<b>b</b>,<b>d</b>) after oxidation at 800 °C (<b>a</b>,<b>b</b>) and 1200 °C (<b>c</b>,<b>d</b>). The size of each oxidation specimen was 3 × 3 × 3 mm<sup>3</sup>.</p> Full article ">Figure 8
<p>BSE images of the microstructure (<b>a</b>) of a cross section of the oxidized alloy JZ2, (<b>b</b>) of the oxide scale, (<b>c</b>,<b>d</b>) of the diffusion zones 1 and 2, respectively. For the region indicated by a rectangle in (<b>d</b>), see later on the Figure 10 and text.</p> Full article ">Figure 9
<p>BSE image and X-ray maps of a region in diffusion zone 1.</p> Full article ">Figure 10
<p>BSE image and X-ray maps of the rectangular region in <a href="#materials-13-01778-f008" class="html-fig">Figure 8</a>d.</p> Full article ">
10 pages, 4993 KiB  
Article
Sensing Ability of Ferroelectric Oxide Nanowires Grown in Templates of Nanopores
by Mariya Aleksandrova, Tsvetozar Tsanev, Ashish Gupta, Ajaya Kumar Singh, Georgi Dobrikov and Valentin Videkov
Materials 2020, 13(7), 1777; https://doi.org/10.3390/ma13071777 - 10 Apr 2020
Cited by 6 | Viewed by 2437
Abstract
Nanowires of ferroelectric potassium niobate were grown by filling nanoporous templates of both side opened anodic aluminum oxide (AAO) through radiofrequency vacuum sputtering for multisensor fabrication. The precise geometrical ordering of the AAO matrix led to well defined single axis oriented wire-shaped material [...] Read more.
Nanowires of ferroelectric potassium niobate were grown by filling nanoporous templates of both side opened anodic aluminum oxide (AAO) through radiofrequency vacuum sputtering for multisensor fabrication. The precise geometrical ordering of the AAO matrix led to well defined single axis oriented wire-shaped material inside the pores. The sensing abilities of the samples were studied and analyzed in terms of piezoelectric and pyroelectric response and the results were compared for different length of the nanopores (nanotubes)—1.3 µm, 6.3 µm and 10 µm. Based on scanning electronic microscopy, elemental and microstructural analyses, as well as electrical measurements at bending and heating, the overall sensing performance of the devices was estimated. It was found that the produced membrane type elements, consisting potassium niobate grown in AAO template exhibited excellent piezoelectric response due to the increased specific area as compared to non-structured films, and could be further enhanced with the nanowires length. The piezoelectric voltage increased linearly with 16 mV per micrometer of nanowire’s length. At the same time the pyroelectric voltage was found to be less sensitive to the nanowires length, changing its value at 400 nV/µm. This paper provides a simple and low-cost approach for nanostructuring ferroelectric oxides with multisensing application, and serves as a base for further optimization of template based nanostructured devices. Full article
(This article belongs to the Section Electronic Materials)
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Graphical abstract
Full article ">Figure 1
<p>SEM image showing top view of uncoated sample with potassium niobate anodic aluminum oxide (AAO) pores.</p> Full article ">Figure 2
<p>SEM images of the top view of the AAO pores with different filling degrees (different times of sputtering of KNbO<sub>3</sub>): (<b>a</b>) after 30 min of sputtering the pores are still open; (<b>b</b>) after 45 min the pores tend to be filled, but they are still partially open; (<b>c</b>) after 60 min of sputtering the pores are fully closed; (<b>d</b>) distribution of the nanopores diameters and cell areas; (<b>e</b>) distribution of the nanopores’ diameters and distance in between; (<b>f</b>) distribution of the nanowires’ diameters.</p> Full article ">Figure 3
<p>Cross section of nanowires with different length: (<b>a</b>) 1.3 µm; (<b>b</b>) 6.3 µm; (<b>c</b>) 10 µm.</p> Full article ">Figure 4
<p>EDS analysis of AAO nanopores filled by KNbO<sub>3</sub>: (<b>a</b>) elements presented in the nanopores; (<b>b</b>) distribution of the elements inside the AAO nanotubes along their length.</p> Full article ">Figure 5
<p>RMS voltage of AAO template-based sensor as a function of the mass load at 50 Hz.</p> Full article ">Figure 6
<p>Piezoelectric voltage as a function of the piezoelectric nanowire length at constant mass load.</p> Full article ">Figure 7
<p>XRD patterns of KNbO<sub>3</sub> nanowires with length 1.3 µm and 10 µm produced by AAO template.</p> Full article ">Figure 8
<p>Generated voltage from element AAO/KNbO<sub>3</sub> with different piezoelectric nanowires length at multiple press-release excitations: (<b>a</b>) 1.3 µm; (<b>b</b>) 6.3 µm; (<b>c</b>) 10 µm.</p> Full article ">Figure 9
<p>Pyroelectric coefficient of the KNbO<sub>3</sub> nanowires as functions of their length.</p> Full article ">
10 pages, 1291 KiB  
Article
Enzyme Immobilization on Maghemite Nanoparticles with Improved Catalytic Activity: An Electrochemical Study for Xanthine
by Massimiliano Magro, Davide Baratella, Andrea Venerando, Giulia Nalotto, Caroline R. Basso, Simone Molinari, Gabriella Salviulo, Juri Ugolotti, Valber A. Pedrosa and Fabio Vianello
Materials 2020, 13(7), 1776; https://doi.org/10.3390/ma13071776 - 10 Apr 2020
Cited by 9 | Viewed by 2945
Abstract
Generally, enzyme immobilization on nanoparticles leads to nano-conjugates presenting partially preserved, or even absent, biological properties. Notwithstanding, recent research demonstrated that the coupling to nanomaterials can improve the activity of immobilized enzymes. Herein, xanthine oxidase (XO) was immobilized by self-assembly on peculiar naked [...] Read more.
Generally, enzyme immobilization on nanoparticles leads to nano-conjugates presenting partially preserved, or even absent, biological properties. Notwithstanding, recent research demonstrated that the coupling to nanomaterials can improve the activity of immobilized enzymes. Herein, xanthine oxidase (XO) was immobilized by self-assembly on peculiar naked iron oxide nanoparticles (surface active maghemite nanoparticles, SAMNs). The catalytic activity of the nanostructured conjugate (SAMN@XO) was assessed by optical spectroscopy and compared to the parent enzyme. SAMN@XO revealed improved catalytic features with respect to the parent enzyme and was applied for the electrochemical studies of xanthine. The present example supports the nascent knowledge concerning protein conjugation to nanoparticle as a means for the modulation of biological activity. Full article
(This article belongs to the Special Issue Advanced Functional Nanostructured Biosensors)
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<p>Characterization of the SAMN@XO complex. (<b>A</b>) Determination of the amount of xanthine oxidase bound on SAMNs as a function of nanoparticle concentration. (<b>B</b>) TEM image of the SAMN@XO hybrid.</p> Full article ">Figure 2
<p>UV-Vis spectra of naked SAMNs and of the SAMN@XO complex. Measurements were carried out in water. Solid line: 0.1 g L<sup>−1</sup> naked SAMNs; Dashed line: 0.1 g L<sup>−1</sup> SAMN@XO.</p> Full article ">Figure 3
<p>Comparison of enzymatic activity of native (black line) and immobilized Xanthine Oxidase (red line). Measurements were carried out in 50 mM potassium phosphate buffer, pH 7.5, at 25 °C in the presence of 51 nM XO (0.25 mg mL<sup>−1</sup> SAMN@XO, 60 µg XO mg<sup>−1</sup> SAMNs).</p> Full article ">Figure 4
<p>Cyclic voltammetry of graphite screen-printed electrodes (GSPEs) modified with SAMNs in the presence of xanthine (<b>A</b>) and uric acid (<b>B</b>). Measurements were carried out by dropping 2 µL of a suspension of 0.25 mg mL<sup>−1</sup> SAMN in 50 mM phosphate buffer, pH 7.5. Scan speed, 20 mV s<sup>−1</sup>. Black line: no substrate.</p> Full article ">Figure 5
<p>Square wave voltammetries and calibration plot obtained with SAMN@XO magnetically immobilized on a graphite screen-printed electrode as a function of xanthine concentration. Measurements were carried out in triplicate on the same sensor obtained by dropping 2 µL of a SAMN@XO suspension (0.25 mg mL<sup>−1</sup>) in 50 mM phosphate buffer, pH 7.5. Error bars in the inset represent standard deviations.</p> Full article ">
24 pages, 6715 KiB  
Article
Optimization the Process of Chemically Modified Carbon Nanofiber Coated Monolith via Response Surface Methodology for CO2 Capture
by Mohamad Rasool Malekbala, Soroush Soltani, Suraya Abdul Rashid, Luqman Chuah Abdullah, Umer Rashid, Imededdine Arbi Nehdi, Thomas Shean Yaw Choong and Siow Hwa Teo
Materials 2020, 13(7), 1775; https://doi.org/10.3390/ma13071775 - 10 Apr 2020
Cited by 9 | Viewed by 2770
Abstract
In the present study, a sequence of experiments was performed to assess the influence of the key process parameters on the formation of a carbon nanofiber-coated monolith (CNFCM), using a four-level factorial design in response surface methodology (RSM). The effect of reaction temperature, [...] Read more.
In the present study, a sequence of experiments was performed to assess the influence of the key process parameters on the formation of a carbon nanofiber-coated monolith (CNFCM), using a four-level factorial design in response surface methodology (RSM). The effect of reaction temperature, hydrocarbon flow rate, catalyst and catalyst promoter were examined using RSM to enhance the formation yield of CNFs on a monolith substrate. To calculate carbon yield, a quadratic polynomial model was modified through multiple regression analysis and the best possible reaction conditions were found as follows: a reaction temperature of 800 °C, furfuryl alcohol flow of 0.08525 mL/min, ferrocene catalyst concentration of 2.21 g. According to the characterization study, the synthesized CNFs showed a high graphitization which were uniformly distributed on a monolith substrate. Besides this, the feasibility of carbon dioxide (CO2) adsorption from the gaseous mixture (N2/CO2) under a range of experimental conditions was investigated at monolithic column. To get the most out of the CO2 capture, an as-prepared sample was post-modified using ammonia. Furthermore, a deactivation model (DM) was introduced for the purpose of studying the breakthrough curves. The CO2 adsorption onto CNFCM was experimentally examined under following operating conditions: a temperature of 30–50 °C, pressure of 1–2 bar, flow rate of 50–90 mL/min, and CO2 feed amount of 10–40 vol.%. A lower adsorption capacity and shorter breakthrough time were detected by escalating the temperature. On the other hand, the capacity for CO2 adsorption increased by raising the CO2 feed amount, feed flow rate, and operating pressure. The comparative evaluation of CO2 uptake over unmodified and modified CNFCM adsorbents confirmed that the introduced modification procedure caused a substantial improvement in CO2 adsorption. Full article
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<p>A graphical illustration of the experimental set-up for adsorption of carbon dioxide (CO<sub>2</sub>).</p> Full article ">Figure 2
<p>3D wireframe surface plot and contour plot: Interaction effect of factors on carbon nanofiber (CNF) yield (%). Contour Plot of Interactions between Temperature and Catalyst Weight (<b>a</b>), Temperature and Hydrocarbon Flow Rate (<b>c</b>), Temperature and Catalyst Promoter Concentration (<b>e</b>), Hydrocarbon Flow Rate and Catalyst Weight (<b>g</b>), Catalyst Promoter Concentration and catalyst weight (<b>i</b>), Catalyst Promoter Concentration and Hydrocarbon Flow Rate (<b>k</b>), and 3D Wireframe Surface Plot of the Interactions between Temperature and Catalyst Weight (<b>b</b>), Temperature and Hydrocarbon Flow Rate (<b>d</b>), Temperature and Catalyst Promoter Concentration (<b>f</b>), Hydrocarbon Flow Rate and Catalyst Weight (<b>h</b>), Catalyst Promoter Concentration and Catalyst Weight (<b>j</b>), Catalyst Promoter Concentration and Hydrocarbon Flow Rate (<b>l</b>) on Yield of CNF.</p> Full article ">Figure 2 Cont.
<p>3D wireframe surface plot and contour plot: Interaction effect of factors on carbon nanofiber (CNF) yield (%). Contour Plot of Interactions between Temperature and Catalyst Weight (<b>a</b>), Temperature and Hydrocarbon Flow Rate (<b>c</b>), Temperature and Catalyst Promoter Concentration (<b>e</b>), Hydrocarbon Flow Rate and Catalyst Weight (<b>g</b>), Catalyst Promoter Concentration and catalyst weight (<b>i</b>), Catalyst Promoter Concentration and Hydrocarbon Flow Rate (<b>k</b>), and 3D Wireframe Surface Plot of the Interactions between Temperature and Catalyst Weight (<b>b</b>), Temperature and Hydrocarbon Flow Rate (<b>d</b>), Temperature and Catalyst Promoter Concentration (<b>f</b>), Hydrocarbon Flow Rate and Catalyst Weight (<b>h</b>), Catalyst Promoter Concentration and Catalyst Weight (<b>j</b>), Catalyst Promoter Concentration and Hydrocarbon Flow Rate (<b>l</b>) on Yield of CNF.</p> Full article ">Figure 2 Cont.
<p>3D wireframe surface plot and contour plot: Interaction effect of factors on carbon nanofiber (CNF) yield (%). Contour Plot of Interactions between Temperature and Catalyst Weight (<b>a</b>), Temperature and Hydrocarbon Flow Rate (<b>c</b>), Temperature and Catalyst Promoter Concentration (<b>e</b>), Hydrocarbon Flow Rate and Catalyst Weight (<b>g</b>), Catalyst Promoter Concentration and catalyst weight (<b>i</b>), Catalyst Promoter Concentration and Hydrocarbon Flow Rate (<b>k</b>), and 3D Wireframe Surface Plot of the Interactions between Temperature and Catalyst Weight (<b>b</b>), Temperature and Hydrocarbon Flow Rate (<b>d</b>), Temperature and Catalyst Promoter Concentration (<b>f</b>), Hydrocarbon Flow Rate and Catalyst Weight (<b>h</b>), Catalyst Promoter Concentration and Catalyst Weight (<b>j</b>), Catalyst Promoter Concentration and Hydrocarbon Flow Rate (<b>l</b>) on Yield of CNF.</p> Full article ">Figure 3
<p>Correspondence plot of predicted and actual values of CNF yield (%).</p> Full article ">Figure 4
<p>FE-SEM images of the carbon nanofiber-coated monoliths (CNFCMs) synthesized at various temperatures (<b>a</b> and <b>b</b>) 600 °C, (<b>c</b> and <b>d</b>) 700 °C, (<b>e</b> and <b>f</b>) 800 °C, (<b>g</b> and <b>h</b>) 900 °C. Red arrow: iron catalyst.</p> Full article ">Figure 5
<p>Raman spectra of the CNFCMs synthesized at various temperatures.</p> Full article ">Figure 6
<p>FE-SEM images of CNFs prepared with different ferrocene concentrations: (<b>a</b>) ferrocene (1.00 g), (<b>b</b>) ferrocene (2.21 g), (<b>c</b>) ferrocene (3.00 g).</p> Full article ">Figure 7
<p>Raman spectra of CNFs prepared with different ferrocene concentrations.</p> Full article ">Figure 8
<p>EDX analysis of (<b>a</b>) CNFCM and (<b>b</b>) modified CNFCM.</p> Full article ">Figure 9
<p>N<sub>2</sub> ads–des isotherm of CNFCM and modified CNFCM.</p> Full article ">Figure 10
<p>FTIR spectrums of CNFCM and modified CNFCM prepared over the following reaction conditions: reaction temperature of 800 °C, furfuryl alcohol flow of 0.08525 mL/min, ferrocene catalyst concentration of 2.21 g.</p> Full article ">Figure 11
<p>Breakthrough curve and effect of flow rate of (<b>a</b>) CNFCM and (<b>b</b>) modified CNFCM in constant T = 30 °C, P = 1 bar and 10% CO<sub>2.</sub></p> Full article ">Figure 12
<p>Breakthrough curve and effect of initial concentration (<b>a</b>) CNFCM and (<b>b</b>) modified CNFCM in constant T = 30 °C, P = 1 bar and Flow = 50 mL/min.</p> Full article ">Figure 13
<p>Breakthrough curve and effect of temperature (<b>a</b>) CNFCM and (<b>b</b>) Modified CNFCM in constant P = 1 bar, and 10% CO<sub>2.</sub></p> Full article ">Figure 14
<p>Breakthrough curve and effect of pressure (<b>a</b>) CNFCM and (<b>b</b>) modified CNFCM in constant T = 30 °C, Flow = 50 mL/min, and 10% CO<sub>2.</sub></p> Full article ">Figure 15
<p>Breakthrough curves adsorption of CNFCM and modified CNFCM in constant 40% CO<sub>2</sub>, T = 30 °C, P = 1 Bar.</p> Full article ">Figure 16
<p>Cyclic adsorption of CO<sub>2</sub> of CNFCM and MCNCM (40% CO<sub>2</sub>, T = 30 °C, P = 1 Bar).</p> Full article ">
21 pages, 6217 KiB  
Review
Review of Application and Innovation of Geotextiles in Geotechnical Engineering
by Hao Wu, Chongkai Yao, Chenghan Li, Miao Miao, Yujian Zhong, Yuquan Lu and Tong Liu
Materials 2020, 13(7), 1774; https://doi.org/10.3390/ma13071774 - 10 Apr 2020
Cited by 92 | Viewed by 15369
Abstract
Most geotextiles consist of polymers of polyolefin, polyester or polyamide family, which involve environmental problems related to soil pollution. Geotextiles can be used for at least one of the following functions: Separation, reinforcement, filtration, drainage, stabilization, barrier, and erosion protection. Due to the [...] Read more.
Most geotextiles consist of polymers of polyolefin, polyester or polyamide family, which involve environmental problems related to soil pollution. Geotextiles can be used for at least one of the following functions: Separation, reinforcement, filtration, drainage, stabilization, barrier, and erosion protection. Due to the characteristics of high strength, low cost, and easy to use, geotextiles are widely used in geotechnical engineering such as soft foundation reinforcement, slope protection, and drainage system. This paper reviews composition and function of geotextiles in geotechnical engineering. In addition, based on literatures including the most recent data, the discussion turns to recent development of geotextiles, with emphasis on green geotextiles, intelligent geotextiles, and high-performance geotextiles. The present situation of these new geotextiles and their application in geotechnical engineering are reviewed. Full article
(This article belongs to the Special Issue Novel Sustainable Technologies for Recycling Waste Materials)
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<p>Most common polymers used as geotextiles and SEM image.</p> Full article ">Figure 2
<p>Separation function of geotextiles.</p> Full article ">Figure 3
<p>Comparison of pavement with or without geotextiles.</p> Full article ">Figure 4
<p>Filtration function of geotextiles.</p> Full article ">Figure 5
<p>Drainage function of geotextiles.</p> Full article ">Figure 6
<p>Subsurface drainage design with the wicking geotextiles [<a href="#B35-materials-13-01774" class="html-bibr">35</a>].</p> Full article ">Figure 7
<p>Reinforcement function of geotextiles.</p> Full article ">Figure 8
<p>Some applications of geotextile reinforcement: (<b>a</b>) reinforcement of slopes; (<b>b</b>) reinforcement of embankment; (<b>c</b>) reinforcement of soft soil foundation; and (<b>d</b>) reinforcement of load transfer platforms.</p> Full article ">Figure 9
<p>Global geotextile market share, by application, 2019 (%) [<a href="#B41-materials-13-01774" class="html-bibr">41</a>,<a href="#B42-materials-13-01774" class="html-bibr">42</a>,<a href="#B43-materials-13-01774" class="html-bibr">43</a>].</p> Full article ">Figure 10
<p>Chemical structure and properties of main components in plant fiber [<a href="#B5-materials-13-01774" class="html-bibr">5</a>].</p> Full article ">Figure 11
<p>Common natural-fiber-based geotextiles: (<b>a</b>) jute geotextiles and (<b>b</b>) coir geotextiles.</p> Full article ">Figure 12
<p>Soluble heavy metals breakthrough curves (BTCs): (<b>a</b>) sand alone and (<b>b</b>) sand + 3 flax geotextile [<a href="#B80-materials-13-01774" class="html-bibr">80</a>].</p> Full article ">Figure 13
<p>The working principle and sensing principle of Fiber Bragg grating (FBG) [<a href="#B104-materials-13-01774" class="html-bibr">104</a>].</p> Full article ">Figure 14
<p>Intelligent geotextile based on distributed sensor.</p> Full article ">Figure 15
<p>Intelligent geotextile based on polymer optical fiber sensor.</p> Full article ">Figure 16
<p>(<b>a</b>) intelligent geotextiles installed and (<b>b</b>) test site [<a href="#B113-materials-13-01774" class="html-bibr">113</a>].</p> Full article ">
10 pages, 2621 KiB  
Article
Reduced Graphene Oxide-Based Impedimetric Immunosensor for Detection of Enterotoxin A in Milk Samples
by Giovanna S. Rocha, Martin K. L. Silva and Ivana Cesarino
Materials 2020, 13(7), 1751; https://doi.org/10.3390/ma13071751 - 10 Apr 2020
Cited by 15 | Viewed by 2874
Abstract
A simple, cheap, and less aggressive immobilization procedure for biomolecules using reduced graphene oxide (rGO) was employed to prepare an impedimetric immunosensor for detection of staphylococcal enterotoxin A (SEA) from Staphylococcus aureus in milk samples. The scanning electron microscopy, cyclic voltammetry, and electrochemical [...] Read more.
A simple, cheap, and less aggressive immobilization procedure for biomolecules using reduced graphene oxide (rGO) was employed to prepare an impedimetric immunosensor for detection of staphylococcal enterotoxin A (SEA) from Staphylococcus aureus in milk samples. The scanning electron microscopy, cyclic voltammetry, and electrochemical impedance spectroscopy (EIS) were used to monitor the single steps of the electrode assembly process. The glassy carbon (GC)/rGO platform detected the antigen-antibody binding procedures of SEA with concentrations of 0.5 to 3.5 mg L−1 via impedance changes in a low frequency range. The impedimetric immunosensor was successfully applied for the determination of SEA in milk samples. Full article
(This article belongs to the Special Issue Advanced Functional Nanostructured Biosensors)
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<p>Schematic representation of reduced graphene oxide synthesis procedure.</p> Full article ">Figure 2
<p>Schematic representation of the SEA immunosensor fabrication on a GC electrode.</p> Full article ">Figure 3
<p>SEM micrographs for GO (<b>A</b>) and rGO (<b>B</b>) materials.</p> Full article ">Figure 4
<p>Cyclic voltammograms (<b>A</b>) and Nyquist plots (<b>B</b>) for: (a) GC/rGO, (b) GC/rGO/anti-SEA, (c) GC/rGO/anti-SEA/BSA and (d) GC/rGO/anti-SEA/BSA/SEA. Both experiments were performed in a 0.2 mol L<sup>−1</sup> PBS (pH 7.4) solution containing 0.1 mol L<sup>−1</sup> of KCl and 5.0 mmol L<sup>−1</sup> of Fe(CN)<sub>6</sub>]<sup>3−/4−</sup>. <span class="html-italic">Inset</span>: equivalent circuit.</p> Full article ">Figure 5
<p>Responses of the proposed immunosensor to a fixed amount of SEA using different concentrations of antibody ranging from 0.030 to 0.105 mg mL<sup>−1</sup> (<b>A</b>) and successive measurements of the sensor with immobilized antibody (<b>B</b>).</p> Full article ">Figure 6
<p>Nyquist plots of the immunosensor incubated with different SEA concentrations (<b>A</b>) and respective calibration curve from 0.5 to 3.5 mg L<sup>−1</sup> (<b>B</b>).</p> Full article ">
15 pages, 5309 KiB  
Article
3D Printing of Piezoelectric Barium Titanate-Hydroxyapatite Scaffolds with Interconnected Porosity for Bone Tissue Engineering
by Christian Polley, Thomas Distler, Rainer Detsch, Henrik Lund, Armin Springer, Aldo R. Boccaccini and Hermann Seitz
Materials 2020, 13(7), 1773; https://doi.org/10.3390/ma13071773 - 9 Apr 2020
Cited by 98 | Viewed by 9480
Abstract
The prevalence of large bone defects is still a major problem in surgical clinics. It is, thus, not a surprise that bone-related research, especially in the field of bone tissue engineering, is a major issue in medical research. Researchers worldwide are searching for [...] Read more.
The prevalence of large bone defects is still a major problem in surgical clinics. It is, thus, not a surprise that bone-related research, especially in the field of bone tissue engineering, is a major issue in medical research. Researchers worldwide are searching for the missing link in engineering bone graft materials that mimic bones, and foster osteogenesis and bone remodeling. One approach is the combination of additive manufacturing technology with smart and additionally electrically active biomaterials. In this study, we performed a three-dimensional (3D) printing process to fabricate piezoelectric, porous barium titanate (BaTiO3) and hydroxyapatite (HA) composite scaffolds. The printed scaffolds indicate good cytocompatibility and cell attachment as well as bone mimicking piezoelectric properties with a piezoelectric constant of 3 pC/N. This work represents a promising first approach to creating an implant material with improved bone regenerating potential, in combination with an interconnected porous network and a microporosity, known to enhance bone growth and vascularization. Full article
(This article belongs to the Special Issue Bioceramic Composites for Biomedical Applications)
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Full article ">Figure 1
<p>Overview of 3D printing of piezoelectric materials for bone stimulating implants. (<b>A</b>) shows exemplarily the binder jetting process used for the fabrication of piezoelectric scaffolds. (<b>B</b>) indicates different applications of the piezoelectric effect for bone stimulation. Piezoelectric implants have the potential to stimulate electrically (direct piezoelectric effect), mechanically (indirect piezoelectric effect) or could be used as an energy harvesting device to power other implants or sensors.</p> Full article ">Figure 2
<p>CAD Design and geometrical data of BaTiO<sub>3</sub>/HA composite scaffolds.</p> Full article ">Figure 3
<p>Applicated debinding, (<b>A</b>) and sintering curve, (<b>B</b>) for 3D printed BaTiO<sub>3</sub>/HA composite scaffolds.</p> Full article ">Figure 4
<p>SEM image of the BaTiO<sub>3</sub>/HA powder mixture used for the 3DP process (<b>A</b>, scale bar: 20 µm). Elementary classification by EDX spectroscopy for HA (<b>B</b>, scale bar: 90 µm) and BaTiO<sub>3</sub> (<b>C</b>, Scale bar: 90 µm).</p> Full article ">Figure 5
<p>Three-dimensional (3D) printed cylindrical and interconnected scaffolds from BaTiO<sub>3</sub>/HA composite prior to debinding and sintering (<b>A</b>, scale bar: 10 mm) and afterward (<b>B</b>, scale bar: 10 mm). The shrinkage of the BaTiO<sub>3</sub>/HA scaffolds classified into fabrication process (3DP) and sintering, representing the fidelity of the printing process and the impact of thermal post-treatment (<b>C</b>).</p> Full article ">Figure 6
<p>(<b>A</b>) Three-dimensional maximum intensity projection (MIP) of a BaTiO<sub>3</sub>/HA scaffolds with visible particles of different densities (scale bar: 2 mm); (<b>B</b>) The binarised cross-sectional microCT images reveal the number of pores (black) and provide the basis for a 3D calculation of porosity (scale bar: 1 mm). (<b>C</b>) The SEM images underline the results visible in the microCT of a highly porous network of particles which are roughly sintered. Large particles of HA are embedded in a percolating network of BaTiO<sub>3</sub> particles through the whole scaffold (scale bar: 2 µm); (<b>D</b>) The pore size distribution of a 3D printed BaTiO<sub>3</sub>/HA scaffold.</p> Full article ">Figure 7
<p>Powder diffraction pattern of 3D printed and sintered BaTiO<sub>3</sub>/HA scaffold and reference data: pdf 01-076-8436 (ICDD, 2016, hydroxyapatite), 01-081-8524 (ICDD, 2016, BaTiO<sub>3</sub>, tetragonal), and 01-081-8527 (ICDD, 2016, BaTiO<sub>3</sub>, cubic), respectively. Reference data is shown in relative intensities. Cu Kα<sub>2</sub> radiation has been removed arithmetically for clarity.</p> Full article ">Figure 8
<p>Piezoelectric coefficient d<sub>33</sub> in dependence of the applied polarization field (<b>A</b>) and polarization time (<b>B</b>).</p> Full article ">Figure 9
<p>Indirect in-vitro cytotoxicity test according to ISO 10993 using material eluates. (<b>A</b>) LIVE/DEAD Images of Calcein AM (green, live) and propidium Iodide (red, dead) stained MC3T3-E1 cells after 24 h of incubation on tissue culture polystyrene (TCPS) with cell culture medium (pos. control), BaTiO<sub>3</sub>/HA scaffolds eluates. Scale bars: 200 µm, 50 µm (detail). (<b>B</b>) Quantification of LIVE/DEAD data as area of live cells (%) per FM image (n &gt; 4 biological replicates, n = 3 images) normalized to TCPS reference substrates. (<b>C</b>) Indirect cell viability test (WST-8) (n ≥ 4 biological replicates) measured as the absorbance at 450 nm as an indicator for cell viability. (<b>D</b>) Intracellular LDH level as a measure of cell death and proliferation (n = 4 biological replicates). Data are shown as mean ±SD. Statistically significant differences were analyzed using one-way ANOVA analysis, with no significant difference indicated (NS).</p> Full article ">Figure 10
<p>Direct in-vitro cytocompatibility test of MC3T3-E1 cells after 24 h of incubation on BaTiO<sub>3</sub>/HA. (<b>A</b>) LIVE/DEAD Images of Calcein AM (green, live) and propidium Iodide (red, dead) stained MC3T3-E1 cells after 24 h of direct incubation on TCPS and BaTiO<sub>3</sub>/HA scaffolds. Scale bars: 200 µm, 50 µm (detail). (<b>B</b>) Quantification of LIVE/DEAD data as the area of live cells (%) per image (n &gt; 4 biological replicates, n = 3 images) normalized to tissue culture polystyrene reference substrates. (<b>C</b>) Indirect cell viability test (WST-8) (n = 12 biological replicates) measured as the absorbance at 450 nm of metabolized tetrazolim salt to a soluble formazan as an indicator of cell viability. (<b>D</b>) Extracellular LDH levels as a measure of cell death, respectively (n ≥ 3 biological replicates). LDH levels with no statistically significant difference were analyzed using the non-parametric Mann-Whitney U test (NS, p &lt; 0.05). Data is shown as mean ±SD. NS indicated no significant difference (p &lt; 0.05) between groups using Welch‘s t-test.</p> Full article ">Figure 11
<p>SEM images of MC3T3-E1 cells after 24 h of incubation on BaTiO<sub>3</sub>/HA scaffolds. Representative SEM images of MC3T3-E1 cell-material interaction with BaTiO<sub>3</sub>/HA substrates. Scale bars: 20 µm (<b>A</b>), 4 µm (<b>B</b>).</p> Full article ">
14 pages, 6513 KiB  
Article
Polydopamine-Modified Al2O3/Polyurethane Composites with Largely Improved Thermal and Mechanical Properties
by Ruikui Du, Li He, Peng Li and Guizhe Zhao
Materials 2020, 13(7), 1772; https://doi.org/10.3390/ma13071772 - 9 Apr 2020
Cited by 24 | Viewed by 4054
Abstract
Alumina/polyurethane composites were prepared via in situ polymerization and used as thermal interface materials (TIMs). The surface of alumina particles was modified using polydopamine (PDA) and then evaluated via Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG), and Raman spectroscopy (Raman). Scanning electron [...] Read more.
Alumina/polyurethane composites were prepared via in situ polymerization and used as thermal interface materials (TIMs). The surface of alumina particles was modified using polydopamine (PDA) and then evaluated via Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG), and Raman spectroscopy (Raman). Scanning electron microscope (SEM) images showed that PDA-Al2O3 has better dispersion in a polyurethane (PU) matrix than Al2O3. Compared with pure PU, the 30 wt% PDA-Al2O3/PU had 95% more Young’s modulus, 128% more tensile strength, and 76% more elongation at break than the pure PU. Dynamic mechanical analysis (DMA) results showed that the storage modulus of the 30 wt% PDA-Al2O3/PU composite improved, and the glass transition temperature (Tg) shifted to higher temperatures. The thermal conductivity of the 30 wt% PDA-Al2O3/PU composite increased by 138%. Therefore, the results showed that the prepared PDA-coated alumina can simultaneously improve both the mechanical properties and thermal conductivity of PU. Full article
(This article belongs to the Section Advanced Composites)
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Figure 1
<p>SEM images of pristine Al<sub>2</sub>O<sub>3</sub>.</p> Full article ">Figure 2
<p>Scheme of modification of pristine Al<sub>2</sub>O<sub>3</sub> surface using polydopamine (PDA).</p> Full article ">Figure 3
<p>Preparation of polyurethane (PU) composites filled with Al<sub>2</sub>O<sub>3</sub> and PDA-Al<sub>2</sub>O<sub>3</sub>.</p> Full article ">Figure 4
<p>FTIR results for Al<sub>2</sub>O<sub>3</sub> and PDA-Al<sub>2</sub>O<sub>3</sub>.</p> Full article ">Figure 5
<p>Thermogravimetric analysis (TGA) results for Al<sub>2</sub>O<sub>3</sub> and PDA-Al<sub>2</sub>O<sub>3</sub>.</p> Full article ">Figure 6
<p>Raman results for Al<sub>2</sub>O<sub>3</sub> and PDA-Al<sub>2</sub>O<sub>3</sub>.</p> Full article ">Figure 7
<p>SEM morphology of composites filled with (<b>a</b>) 30 wt% Al<sub>2</sub>O<sub>3</sub>, (<b>b</b>) 30 wt% PDA-Al<sub>2</sub>O<sub>3</sub>, EDS element distribution of yellow spots in (<b>c</b>) 30 wt% Al<sub>2</sub>O<sub>3</sub>/PU, and (<b>d</b>) 30 wt% PDA-Al<sub>2</sub>O<sub>3</sub>/PU.</p> Full article ">Figure 8
<p>Thermal stability of Al<sub>2</sub>O<sub>3</sub>/PU and PDA-Al<sub>2</sub>O<sub>3</sub>/PU composites: (<b>a</b>) TG, (<b>b</b>) DTG curves.</p> Full article ">Figure 9
<p>Thermal conductivity of Al<sub>2</sub>O<sub>3</sub>/PU and PDA-Al<sub>2</sub>O<sub>3</sub>/PU composites.</p> Full article ">Figure 10
<p>The relationship between storage modulus (<b>a</b>) and loss factor (<b>b</b>) of Al<sub>2</sub>O<sub>3</sub>/PU and PDA-Al<sub>2</sub>O<sub>3</sub>/PU composites with respect to temperature.</p> Full article ">Figure 11
<p>Mechanical properties of the Al<sub>2</sub>O<sub>3</sub>/PU and PDA-Al<sub>2</sub>O<sub>3</sub>/PU composites: (<b>a</b>) Young’s modulus, (<b>b</b>) tensile strength, and (<b>c</b>) elongation at the break.</p> Full article ">Figure 12
<p>Water absorption of Al<sub>2</sub>O<sub>3</sub>/PU and PDA-Al<sub>2</sub>O<sub>3</sub>/PU composites.</p> Full article ">
16 pages, 5325 KiB  
Article
Prototype Gastro-Resistant Soft Gelatin Films and Capsules—Imaging and Performance In Vitro
by Bartosz Maciejewski, Vishnu Arumughan, Anette Larsson and Małgorzata Sznitowska
Materials 2020, 13(7), 1771; https://doi.org/10.3390/ma13071771 - 9 Apr 2020
Cited by 3 | Viewed by 3384
Abstract
The following study is a continuation of the previous work on preparation of gastro-resistant films by incorporation of cellulose acetate phthalate (CAP) into the soft gelatin film. An extended investigation on the previously described binary Gelatin-CAP and ternary Gelatin-CAP-carrageenan polymer films was performed. [...] Read more.
The following study is a continuation of the previous work on preparation of gastro-resistant films by incorporation of cellulose acetate phthalate (CAP) into the soft gelatin film. An extended investigation on the previously described binary Gelatin-CAP and ternary Gelatin-CAP-carrageenan polymer films was performed. The results suggest that the critical feature behind formation of the acid-resistant films is a spinodal decomposition in the film-forming mixture. In the obtained films, upon submersion in an acidic medium, gelatin swells and dissolves, exposing a CAP-based acid-insoluble skeleton, partially coated by a residue of other ingredients. The dissolution-hindering effect appears to be stronger when iota-carrageenan is added to the film-forming mixture. The drug release study performed in enhancer cells confirmed that diclofenac sodium is not released in the acidic medium, however, at pH 6.8 the drug release occurs. The capsules prepared with a simple lab-scale process appear to be resistant to disintegration of the shell structure in acid, although imperfections of the sealing have been noticed. Full article
(This article belongs to the Special Issue Advanced Materials in Drug Release and Drug Delivery Systems)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Capsule formation scheme.</p> Full article ">Figure 2
<p>The enhancer cell with gelatin + Aquacoat + carrageenan (GAC) film.</p> Full article ">Figure 3
<p>SEM image of GA and GAC films after 2 h in 0.1 M HCl. Scale bar: (<b>a</b>) 10 µm, (<b>b</b>) 1 µm.</p> Full article ">Figure 4
<p>Confocal laser scanning microscopy (CLSM) images of GA film after 2 h immersion in 0.1M HCl: surface layer (<b>a</b>) and the inner central part (<b>b</b>) of the film.</p> Full article ">Figure 5
<p>The Raman spectra of several points examined on the surface of GAC film: (<b>a</b>) before immersion in acid; (<b>b</b>) after immersion for 2 h in 0.1M HCl. Multiple overlaid spectra are presented on each graph.</p> Full article ">Figure 6
<p>Comparison of the Raman spectra: (<b>a</b>) untreated and acid-treated GAC; (<b>b</b>) acid-treated GAC and cellulose acetate phthalate (CAP) film (without gelatin). Multiple spectra of each composition are presented.</p> Full article ">Figure 7
<p>The surface morphology of the gelatin film on the quartz crystal microbalance with dissipation (QCM-D) sensor.</p> Full article ">Figure 8
<p>A QCM-D graph obtained at 5th overtone. The approx. 550 Hz drop in frequency carries risk of error on calculating the mass increase: (<b>a</b>) start of latex flow; (<b>b</b>) start of water flow (to remove particles that are not bound to the film).</p> Full article ">Figure 9
<p>SEM images of the cross-sections of the capsule sealing site: (<b>a</b>) an apparently successful sealing; (<b>b</b>) close-up of the area; (<b>c</b>) a reference commercial soft gelatin capsule.</p> Full article ">Figure 10
<p>The effect of the stirring rate in a paddle apparatus on the release profiles of diclofenac sodium from the PEG 400 solution in a diffusion cell closed with GAC film.</p> Full article ">Figure 11
<p>The visible phase-separation on lowering the temperature of the sample, and suspected spinodal decomposition process on storage at 80 °C for a prolonged time.</p> Full article ">
21 pages, 8211 KiB  
Article
Characterization and Simulation of the Bond Response of NSM FRP Reinforcement in Concrete
by Javier Gómez, Lluís Torres and Cristina Barris
Materials 2020, 13(7), 1770; https://doi.org/10.3390/ma13071770 - 9 Apr 2020
Cited by 26 | Viewed by 3422
Abstract
The near-surface mounted (NSM) technique with fiber reinforced polymer (FRP) reinforcement as strengthening system for concrete structures has been broadly studied during the last years. The efficiency of the NSM FRP-to-concrete joint highly depends on the bond between both materials, which is characterized [...] Read more.
The near-surface mounted (NSM) technique with fiber reinforced polymer (FRP) reinforcement as strengthening system for concrete structures has been broadly studied during the last years. The efficiency of the NSM FRP-to-concrete joint highly depends on the bond between both materials, which is characterized by a local bond–slip law. This paper studies the effect of the shape of the local bond–slip law and its parameters on the global response of the NSM FRP joint in terms of load capacity, effective bond length, slip, shear stress, and strain distribution along the bonded length, which are essential parameters on the strengthening design. A numerical procedure based on the finite difference method to solve the governing equations of the FRP-to-concrete joint is developed. Pull-out single shear specimens are tested in order to experimentally validate the numerical results. Finally, a parametric study is performed. The effect of the bond–shear strength slip at the bond strength, maximum slip, and friction branch on the parameters previously described is presented and discussed. Full article
(This article belongs to the Special Issue Advanced Composites: From Materials Characterization to Structural Application)
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<p>Stress equilibrium (<b>a</b>) in the FRP-concrete joint, and (<b>b</b>) in the FRP-adhesive interface.</p> Full article ">Figure 2
<p>Scheme of the discretization along the FRP.</p> Full article ">Figure 3
<p>Flowchart of the numerical procedure.</p> Full article ">Figure 4
<p>Comparison between the analytical and the numerical models.</p> Full article ">Figure 5
<p>Fracture energy obtained from the bond–slip law.</p> Full article ">Figure 6
<p>Comparison of the bond–slip models.</p> Full article ">Figure 7
<p>Comparison of the load–slip curves, (<b>a</b>) shows LD, BL and TSANL models, and (<b>b</b>) shows BLF, BO, and BONP models.</p> Full article ">Figure 8
<p>(<b>a</b>) FRP slip, (<b>b</b>) bond–shear stress, and (<b>c</b>) FRP strains along the bonded length for the different bond–slip models.</p> Full article ">Figure 9
<p>(<b>a</b>) scheme of the set-up for the pull-out single shear test, and (<b>b</b>) picture of the tests.</p> Full article ">Figure 10
<p>Experimental results from the single shear tests.</p> Full article ">Figure 11
<p>Bond–slip law parameters obtained from the load–slip curve for 7.5 mm grooved specimens.</p> Full article ">Figure 12
<p>Experimental bond–slip laws for the NSM with 7.5 mm and 10 mm thickness grooves.</p> Full article ">Figure 13
<p>Comparison between the experimental (continuous lines) and the theoretical (dashed lines) values for the NSM with <b>(a)</b> 10 mm and <b>(b)</b> 7.5 mm groove thickness.</p> Full article ">Figure 14
<p>(<b>a</b>) Load–slip curve, (<b>b</b>) slip along the FRP, (<b>c</b>) bond–shear stress along the FRP, and (<b>d</b>) strains along the FRP for three values of bond–shear strength and a bilinear bond–slip law.</p> Full article ">Figure 15
<p>Variation of P<sub>max</sub> versus τ<sub>max</sub>.</p> Full article ">Figure 16
<p>Variation of L<sub>eff</sub> versus τ<sub>max</sub>.</p> Full article ">Figure 17
<p>Variation of P<sub>max</sub> versus s<sub>1</sub>.</p> Full article ">Figure 18
<p>Variation of Leff versus s<sub>1</sub>.</p> Full article ">Figure 19
<p>Variation of P<sub>max</sub> versus s<sub>f</sub>.</p> Full article ">Figure 20
<p>Variation of <span class="html-italic">L</span><sub>eff</sub> versus <span class="html-italic">s<sub>f</sub></span>.</p> Full article ">Figure 21
<p>Variation of P<sub>max</sub> versus τ<sub>f</sub>.</p> Full article ">
19 pages, 5097 KiB  
Article
Use of ZnAl-Layered Double Hydroxide (LDH) to Extend the Service Life of Reinforced Concrete
by Celestino Gomes, Zahid Mir, Rui Sampaio, Alexandre Bastos, João Tedim, Frederico Maia, Cláudia Rocha and Mário Ferreira
Materials 2020, 13(7), 1769; https://doi.org/10.3390/ma13071769 - 9 Apr 2020
Cited by 38 | Viewed by 5337
Abstract
This work investigated the use of ZnAl-layered double hydroxide (LDH) intercalated with nitrate or nitrite ions for controlling the corrosion of steel in reinforced concrete. The work started by analyzing the stability of the powder in the 1–14 pH range and the capacity [...] Read more.
This work investigated the use of ZnAl-layered double hydroxide (LDH) intercalated with nitrate or nitrite ions for controlling the corrosion of steel in reinforced concrete. The work started by analyzing the stability of the powder in the 1–14 pH range and the capacity for capturing chloride ions in aqueous solutions of different pH. The effect of the ZnAl-LDH on the corrosion of steel was studied in aqueous 0.05 M NaCl solution and in mortars immersed in 3.5% NaCl. It was found that the LDH powders dissolved partially at pH > 12. The LDH was able to capture chloride ions from the external solution, but the process was pH-dependent and stopped at high pH due to the partial dissolution of LDH and the preferential exchange of OH– ions. These results seemed to imply that ZnAl-LDH would not work in the alkaline environment inside the concrete. Nonetheless, preliminary results with mortars containing ZnAl-LDH showed lower penetration of chloride ions and higher corrosion resistance of the steel rebars. Full article
(This article belongs to the Special Issue Self-Healing and Smart Cementitious Construction Materials)
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<p>Scanning electron microscopy (SEM) images of (<b>a</b>) ZnAl-NO<sub>2</sub> with mean particle size ~25 µm, (<b>b</b>) ZnAl-NO<sub>3</sub> with mean particle size ~25 µm, (<b>c</b>) ZnAl-NO<sub>2</sub> with particle size &gt;125 µm, (<b>d</b>) ZnAl-NO<sub>3</sub> with mean particle size &gt;125 µm; (<b>e</b>) particle size distribution of the layered double hydroxide (LDH) powders; (<b>f</b>) XRD diffractograms of the four LDH powders.</p> Full article ">Figure 2
<p>FTIR spectra of ZnAl-NO<sub>3</sub> and ZnAl-NO<sub>2</sub>.</p> Full article ">Figure 3
<p>Mass (%) of undissolved LDH powder after 1 month of immersion in water in the pH range 1 to 14.</p> Full article ">Figure 4
<p>(<b>a</b>) Decrease of chloride concentration of 0.01 M NaCl solution at different pH after the addition of ZnAl-NO<sub>2</sub> (solution volume = 50 mL, 1 g of LDH added at time t = 0); (<b>b</b>) Chloride binding capacity of ZnAl-NO<sub>2</sub> at different pH and chloride concentrations.</p> Full article ">Figure 5
<p>EIS spectra of steel obtained during immersion in (<b>a</b>) 0.05 M NaCl (pH = 13), (<b>b</b>) 0.05 M NaCl (pH = 13) + 0.5% ZnAl-NO<sub>2</sub>, (<b>c</b>) 0.05 M NaCl (pH~6), (<b>d</b>) 0.05 M NaCl + 0.5% ZnAl-NO<sub>2</sub>, (<b>e</b>) 0.05 M NaCl + 0.5% ZnAl-NO<sub>3</sub>, (<b>f</b>) equivalent electric circuits used for describing the impedance response.</p> Full article ">Figure 6
<p>Influence of LDH particle size on the curing time of cement paste (% of LDH with respect to the mass of cement).</p> Full article ">Figure 7
<p>Scheme of mortar with sensors and chloride profiles inside mortar without (REF) and with ZnAl-NO<sub>2</sub>.</p> Full article ">Figure 8
<p>Impedance response of mortars with steel bar immersed in 3.5% NaCl: (<b>a</b>) Mortar without LDH (reference), (<b>b</b>) mortar with 0.3% ZnAl-NO<sub>3</sub> (2% with respect to cement), (<b>c</b>) mortar with 0.3% ZnAl-NO<sub>2</sub> (2% with respect to cement).</p> Full article ">Figure 9
<p>The equivalent electric circuit used for describing the impedance of mortar with a steel bar.</p> Full article ">
21 pages, 5411 KiB  
Article
Extremely-Low-Cycle Fatigue Damage for Beam-to-Column Welded Joints Using Structural Details
by Lizhen Huang, Weilian Qu and Ernian Zhao
Materials 2020, 13(7), 1768; https://doi.org/10.3390/ma13071768 - 9 Apr 2020
Cited by 4 | Viewed by 2776
Abstract
The multiaxial fatigue critical plane method can be used to evaluate the extremely-low-cycle fatigue (ELCF) damage of beam-to-column welded joints in steel frameworks subjected to strong seismic activity. In this paper, fatigue damage models using structural detail parameters are studied. Firstly, the fatigue [...] Read more.
The multiaxial fatigue critical plane method can be used to evaluate the extremely-low-cycle fatigue (ELCF) damage of beam-to-column welded joints in steel frameworks subjected to strong seismic activity. In this paper, fatigue damage models using structural detail parameters are studied. Firstly, the fatigue properties obtained from experiments are adopted to assess ELCF life for steel frameworks. In these experiments, two types of welded specimens, namely, plate butt weld (PB) and cruciform load-carrying groove weld (CLG), are designed according to the structural details of steel beam and box column joints, in which both structural details and welded factors are taken into account. Secondly, experiments are performed on three full-scale steel welded beam-to-column joints to determine the contribution of stress and/or strain to damage parameters. Finally, we introduce a modification of the most popular fatigue damage model of Fatemi and Socie (FS), modified by us in a previous study, for damage evaluation, and compare this with Shang and Wang (SW) in order to examine the applicability of the fatigue properties of PB and CLG. This study shows that the modified FS model using the fatigue properties of CLG can predict the crack initiation life and evaluate the damage of beam-to-column welded joints, and can be subsequently used for further investigation of the damage evolution law. Full article
(This article belongs to the Section Advanced Materials Characterization)
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<p>Design of welded specimens (mm): (<b>a</b>) plate butt (PB); (<b>b</b>) cruciform load-carrying groove (CLG).</p> Full article ">Figure 2
<p>(<b>a</b>)Test equipment; (<b>b</b>) loading history.</p> Full article ">Figure 3
<p>Cyclic stress–strain hysteresis curve.</p> Full article ">Figure 4
<p>Design of specimen (mm): (<b>a</b>) beam-to-column welded joint; (<b>b</b>) welded structural details.</p> Full article ">Figure 5
<p>Test setup configuration.</p> Full article ">Figure 6
<p>von Mises stress distribution nephogram.</p> Full article ">Figure 7
<p>The location of strain rosettes in the specimen.</p> Full article ">Figure 8
<p>Six strain responses of NWB_2 weld. (* in the figure means the peak or valley of the strain).</p> Full article ">Figure 9
<p>Extremely-low-cycle fatigue (ELCF) damage analysis steps.</p> Full article ">Figure 10
<p>The strains on the candidate critical plane in a three-dimensional coordinate system.</p> Full article ">Figure 11
<p>The location of the critical plane: (<b>a</b>) time = 400 s; (<b>b</b>) time = 800 s.</p> Full article ">Figure 12
<p>Strain response on the critical damage plane: (<b>a</b>) shear strain; (<b>b</b>) normal strain.</p> Full article ">Figure 13
<p>Double cyclic rain flow counting: (<b>a</b>) shear strain range; (<b>b</b>) normal strain range. (Red line represents strain responses; blue line represents strain range correlated to double rain flow counting method).</p> Full article ">Figure 14
<p>The load spectra of variable amplitude fatigue: (<b>a</b>) shear strain range; (<b>b</b>) normal strain range.</p> Full article ">Figure 15
<p>Random strain path and its envelope path.</p> Full article ">Figure 16
<p>Strain path and equivalent convex path on the critical plane of NWB_2.</p> Full article ">
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