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Micromachines
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Recent Advances in Lithography
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Recent Advances in Lithography

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D：Materials and Processing".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 3747

Special Issue Editors

Prof. Dr. Sikun Li

E-Mail Website
Guest Editor
Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
Interests: optical and EUV lithography; inspection and metrology for semicondutor application; computational lithography
Prof. Dr. Yayi Wei

E-Mail Website
Guest Editor
Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China
Interests: advanced patterning solutions, including lithographic materials, equipment, simulations and processes

Special Issue Information

Dear Colleagues,

Lithography has been at the forefront of nanofabrication, enabling the development of semiconductor devices, photonic systems, and nanotechnology-based innovations. Over the decades, lithographic technologies have evolved significantly, progressing from traditional optical techniques to leading-edge extreme ultraviolet (EUV) lithography. These advancements have not only enhanced resolution, but have also addressed the growing demands for efficiency and scalability.

This Special Issue aims to explore the latest breakthroughs and emerging trends in lithography, focusing on its critical role in enabling next-generation technologies. Topics include innovations in optical and EUV lithography, computational lithography, and DTCO (design technology co-optimization) for enhancing performances. We welcome contributions on advanced metrology, inspection, and process control techniques that ensure precision and reliability as well. Further areas of interest include novel patterning technologies, such as holographic lithography, directed self-assembly, laser direct write lithography, electron beam lithography, advancements in photoresist, the integration of double patterning or multiple patterning, lithography beyond projection imaging, etc. By addressing these topics, this Special Issue seeks to highlight the multifaceted progresses in lithographic technology and their transformative impact on modern industry.

Prof. Dr. Sikun Li
Prof. Dr. Yayi Wei
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. Micromachines 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 2100 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

  • optical and EUV lithography
  • computational lithography
  • novel patterning technologies–semiconductors, MEMS, NEMS, MOEMS
  • metrology, inspection, and process control for microlithography
  • advances in patterning materials and processes

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Published Papers (4 papers)

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Research

15 pages, 2615 KiB  
Article
An Improved YOLOv5 Model for Lithographic Hotspot Detection
by Mu Lin, Wenjing He, Jiale Liu, Fencheng Li, Jun Luo and Yijiang Shen
Micromachines 2025, 16(5), 568; https://doi.org/10.3390/mi16050568 - 9 May 2025
Viewed by 228
Abstract
The gap between the ever-shrinking feature size of integrated circuits and lithographic manufacturing ability is causing unwanted shape deformations of printed layout patterns. The deformation region with problematic imaging, known as a hotspot (HS), should be detected and corrected before mask manufacturing. In [...] Read more.
The gap between the ever-shrinking feature size of integrated circuits and lithographic manufacturing ability is causing unwanted shape deformations of printed layout patterns. The deformation region with problematic imaging, known as a hotspot (HS), should be detected and corrected before mask manufacturing. In this paper, we propose a hotspot detection method to improve the precision and recall rate of the fatal pinching and bridging error due to the poor printability of certain layout patterns by embedding a spatial attention mechanism into the YOLOv5 model. Additionally, transfer learning and pre-trained techniques are used to expedite training convergence. Simulation results outperform the depth-based or representative machine learning-based methods on the ICCAD 2012 dataset with an average recall rate of 1, a precision rate of 0.8277 and an F1-score of 0.9057. Full article
(This article belongs to the Special Issue Recent Advances in Lithography)
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15 pages, 9597 KiB  
Article
Extreme Ultraviolet Multilayer Defect Profile Parameters Reconstruction via Transfer Learning with Fine-Tuned VGG-16
by Hala Mohammad, Jiawei Li, Bochao Li, Jamilu Tijjani Baraya, Sana Kone, Zhenlong Zhao, Xiaowei Song and Jingquan Lin
Micromachines 2025, 16(5), 541; https://doi.org/10.3390/mi16050541 - 30 Apr 2025
Viewed by 263
Abstract
Extracting defect profile parameters from measured defect images poses a significant challenge in extreme ultraviolet (EUV) multilayer defect metrologies, because these parameters are crucial for assessing defect printing behavior and determining appropriate repair strategies. This paper proposes to reconstruct defect profile parameters from [...] Read more.
Extracting defect profile parameters from measured defect images poses a significant challenge in extreme ultraviolet (EUV) multilayer defect metrologies, because these parameters are crucial for assessing defect printing behavior and determining appropriate repair strategies. This paper proposes to reconstruct defect profile parameters from reflected field intensity images of a phase defect assisted by transfer learning with fine-tuning. These images are generated through simulations using the rigorous finite-difference time-domain (FDTD) method. The VGG-16 pre-trained model, known for its robust feature extraction capability, is adopted and fine-tuned to map the intensity images to the defect profile parameters. The results demonstrate that the proposed approach accurately reconstructs multilayer defect profile parameters, thus providing important information for mask repair strategies. Full article
(This article belongs to the Special Issue Recent Advances in Lithography)
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18 pages, 2780 KiB  
Article
Frequency-Decoupled Dual-Stage Inverse Lithography Optimization via Hierarchical Sampling and Morphological Enhancement
by Jie Zhou, Qingyan Zhang, Haifeng Sun, Chuan Jin, Ji Zhou and Junbo Liu
Micromachines 2025, 16(5), 515; https://doi.org/10.3390/mi16050515 - 27 Apr 2025
Viewed by 206
Abstract
Inverse lithography technology (ILT) plays a pivotal role in advanced semiconductor manufacturing because it enables pixel-level mask modifications, significantly enhances pattern fidelity, and expands process windows. However, traditional gradient-based ILT methods often struggle with the trade-off between imaging fidelity and mask manufacturability due [...] Read more.
Inverse lithography technology (ILT) plays a pivotal role in advanced semiconductor manufacturing because it enables pixel-level mask modifications, significantly enhances pattern fidelity, and expands process windows. However, traditional gradient-based ILT methods often struggle with the trade-off between imaging fidelity and mask manufacturability due to coupled optimization objectives. We propose a frequency-separated dual-stage optimization framework (FD-ILT) that strategically decouples these conflicting objectives by exploiting the inherent low-pass characteristics of lithographic systems. The first stage optimizes low-frequency (LF) components using hierarchical downsampling to generate a high-fidelity continuous transmission mask. This approach reduces computational complexity while refining resolution progressively. The second stage enforces manufacturability by exclusively adjusting high-frequency (HF) features through morphological regularization and progressive binarization penalties while maintaining the mask LF to preserve imaging accuracy. Our method achieves simultaneous control of both aspects by eliminating gradient conflicts between fidelity and manufacturing constraints. The simulation results demonstrate that FD-ILT achieves superior imaging quality and manufacturability compared to conventional gradient-based ILT methods, offering a scalable solution for advanced semiconductor nodes. Full article
(This article belongs to the Special Issue Recent Advances in Lithography)
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10 pages, 2719 KiB  
Article
Using Higher Diffraction Orders to Improve the Accuracy and Robustness of Overlay Measurements
by Shaoyu Liu, Yan Tang, Xiaolong Cheng, Yuliang Long, Jinfeng Jiang, Yu He and Lixin Zhao
Micromachines 2025, 16(3), 347; https://doi.org/10.3390/mi16030347 - 19 Mar 2025
Viewed by 360
Abstract
This paper introduces a method for improving the measurement performance of single wavelength overlay errors by incorporating higher diffraction orders. In this method, to enhance the accuracy and robustness of overlay error detection between layers, the measurement errors introduced by empirical formulas are [...] Read more.
This paper introduces a method for improving the measurement performance of single wavelength overlay errors by incorporating higher diffraction orders. In this method, to enhance the accuracy and robustness of overlay error detection between layers, the measurement errors introduced by empirical formulas are corrected by incorporating higher diffraction orders, based on the differences in the light intensity difference curves for different diffraction orders. This method also expands the range of available wavelengths for selection. The introduction of specially designed overlay error measurement markers enhances the diffraction efficiency of higher diffraction orders to overcome the issue of their weak light intensity, making them difficult to utilize effectively. This paper first conducts a theoretical analysis using scalar diffraction theory, and then demonstrates the feasibility of the design through vector diffraction simulations and optical path simulations. The resulting two-layer marker structure is simple and compatible with existing measurement systems, showing tremendous potential for application at advanced process nodes. Full article
(This article belongs to the Special Issue Recent Advances in Lithography)
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