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Advancements in Nanofabrication: Innovations in Advanced Semiconductor Materials and Processes for Next-Generation Lithography

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Optoelectronics and Optical Materials".

Deadline for manuscript submissions: 10 March 2025 | Viewed by 1241

Special Issue Editors

Department of Chemistry, Faculty of Natural Sciences, Norwegian University of Science and Technology, Trondheim, Norway
Interests: nanofabrication techniques and applications; flexible LEDs

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Guest Editor
Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
Interests: materials chemistry; polymer chemistry; organic synthesis; DFT calculation; catalysis; photochemistry; organometallics
School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Interests: laser lithography; chemical-mechanical polishing; additive manufacturing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Overview:

This Special Issue aims to explore the cutting-edge advancements in nanofabrication, with a specific focus on innovations in advanced semiconductor materials and processes for next-generation lithography. The integration of novel materials and sophisticated processes plays a pivotal role in pushing the boundaries of nanofabrication techniques, impacting various technological domains.

Scope:

We invite contributions that delve into the forefront of nanofabrication technologies, emphasizing advancements in semiconductor materials and processes that directly impact next-generation lithography methods. Topics of interest include, but are not limited to, the development of novel materials, breakthroughs in lithographic techniques, process optimization, and the application of nanofabrication in emerging technologies.

Potential Themes:

Advanced Semiconductor Materials: Explore the latest developments in semiconductor materials such as advanced photoresists, high-index materials, and alternative lithographic materials.

Innovative Lithographic Techniques: Investigate novel approaches and methodologies in lithography, including extreme ultraviolet (EUV) lithography, directed self-assembly, and other emerging techniques.

Process Optimization and Integration: Address challenges and breakthroughs in optimizing nanofabrication processes, as well as strategies for the seamless integration of advanced materials into existing fabrication workflows.

Applications in Emerging Technologies: Showcase the practical applications of nanofabrication innovations in areas such as quantum computing, photonics, bioelectronics, and other cutting-edge technologies.

Submission Guidelines:

Authors are encouraged to submit original research articles, reviews, and perspectives that contribute to the understanding and advancement of nanofabrication technologies. Manuscripts should be prepared in accordance with the journal's guidelines, and submissions will undergo a rigorous peer-review process.

We look forward to receiving your contributions and collectively collating the most recent advances in nanofabrication through innovations in advanced semiconductor materials and processes.

Dr. Sihai Luo
Dr. Jingyuan Deng
Dr. Chun Cao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • nanofabrication
  • next-generation lithography
  • advanced photoresists
  • extreme ultraviolet lithography (EUV)
  • directed self-assembly
  • process optimization
  • photonics
  • nanotechnology applications
  • nanomaterial characterization

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Published Papers (1 paper)

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Research

13 pages, 4948 KiB  
Article
Feature Vector Effectiveness Evaluation for Pattern Selection in Computational Lithography
by Yaobin Feng, Jiamin Liu, Hao Jiang and Shiyuan Liu
Photonics 2024, 11(10), 990; https://doi.org/10.3390/photonics11100990 - 21 Oct 2024
Viewed by 759
Abstract
Pattern selection is crucial for optimizing the calibration process of optical proximity correction (OPC) models in computational lithography. However, it remains a challenge to achieve a balance between representative coverage and computational efficiency. This work presents a comprehensive evaluation of the feature vectors’ [...] Read more.
Pattern selection is crucial for optimizing the calibration process of optical proximity correction (OPC) models in computational lithography. However, it remains a challenge to achieve a balance between representative coverage and computational efficiency. This work presents a comprehensive evaluation of the feature vectors’ (FVs’) effectiveness in pattern selection for OPC model calibration, leveraging key performance indicators (KPIs) based on Kullback–Leibler divergence and distance ranking. Through the construction of autoencoder-based FVs and fast Fourier transform (FFT)-based FVs, we compare their efficacy in capturing critical pattern features. Validation experimental results indicate that autoencoder-based FVs, particularly augmented with the lithography domain knowledge, outperform FFT-based counterparts in identifying anomalies and enhancing lithography model performance. These results also underscore the importance of adaptive pattern representation methods in calibrating the OPC model with evolving complexities. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) The definition of a pattern. (<b>b</b>) The process of pattern collection.</p>
Full article ">Figure 2
<p>Model error distribution of baseline OPC model. The <span class="html-italic">x</span>-axis is a pattern index without solid physical correspondence. Cyan represents 1000 patterns for calibration with 0 outlier patterns. Dark blue is 2425 patterns for verification with 30 outlier patterns.</p>
Full article ">Figure 3
<p>OPC model prediction accuracy improved after adding outliers into the calibration. The <span class="html-italic">x</span>-axis is a pattern index without solid physical correspondence. Cyan represents 1030 patterns for calibration with 0 outlier patterns. Dark blue is 2395 patterns for verification with 0 outlier patterns.</p>
Full article ">Figure 4
<p>The structure of the AE network.</p>
Full article ">Figure 5
<p>The distance ranking result and KL divergence comparison under different FV dimensions: (<b>a</b>) Result for the FV with dimension 49; (<b>b</b>) Result for the FV with dimension 100; (<b>c</b>) Result for the FV with dimension 196; (<b>d</b>) Result for the FV with dimension 400; (<b>e</b>) Result for the FV with dimension 729.</p>
Full article ">Figure 6
<p>The PCA visualization of improved AE (<b>a</b>) and basic AE (<b>b</b>) under dimension 49.</p>
Full article ">
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