Micromachines

Research

Jump to: Review

11 pages, 4507 KB

Open AccessArticle

Ligand Functionality-Dependent Performance of Organotin Carboxylate Resists

by Xiaofei Liu, Tianren Liu, Kaixin Su, Jingxin Lei, Yuanfu Chen, Yuan Chen and Dongxu Yang

Micromachines 2026, 17(1), 1; https://doi.org/10.3390/mi17010001 - 19 Dec 2025

Viewed by 229

Abstract

As metal-containing resists attract increasing research interest in high-resolution lithography, gaining insights into the photochemical mechanisms, particularly in relation to the ligand functionality, is actively demanded. In this work, a controlled pair of organotin carboxylates with analogous structures but different functional groups has [...] Read more.

As metal-containing resists attract increasing research interest in high-resolution lithography, gaining insights into the photochemical mechanisms, particularly in relation to the ligand functionality, is actively demanded. In this work, a controlled pair of organotin carboxylates with analogous structures but different functional groups has been designed and synthesized as deep-ultraviolet (DUV) resists. Both resists demonstrate 90 nm half-pitch resolution and the capability of pattern transfer on carbon-based hard-mask layers. Through various characterizations and comparison of the controlled pair, we propose two competitive reaction paths for the organotin system with olefin groups, which regulate the lithographic sensitivity and dissolution contrast. Our findings highlight the structural adjustability of organotin carboxylates and their potential application as high-resolution and etch-durable DUV resists. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

10 pages, 2882 KB

Open AccessArticle

AI-Assisted Composite Etch Model for MPT

by Yanbin Gong, Fengsheng Zhao, Devin Sima, Wenzhang Li, Yingxiong Guo, Cheming Hu and Shengrui Zhang

Micromachines 2025, 16(12), 1410; https://doi.org/10.3390/mi16121410 - 15 Dec 2025

Viewed by 236

Abstract

For advanced semiconductor nodes, the demand for high-precision patterning of complex foundry circuits drives the widespread use of Lithography-Etch-Lithography-Etch (LELE)—a key Multiple Patterning Technology (MPT)—in Deep Ultraviolet (DUV) processes. However, the interaction between LELE’s two Lithography-Etch (LE) cycles makes it very challenging to [...] Read more.

For advanced semiconductor nodes, the demand for high-precision patterning of complex foundry circuits drives the widespread use of Lithography-Etch-Lithography-Etch (LELE)—a key Multiple Patterning Technology (MPT)—in Deep Ultraviolet (DUV) processes. However, the interaction between LELE’s two Lithography-Etch (LE) cycles makes it very challenging to build a model for etching contour simulation and hotspot detection. This study presents an Artificial Intelligence (AI)-assisted composite etch model to capture inter-LE interactions, which directly outputs the final post-LELE etch contour, enabling Etch Rule Check (ERC)-based simulation detection of After Etch Inspection (AEI) hotspots. In addition, the etch model proposed in this study can also predict the etch bias of different types of pattern (especially complex two-dimensional (2D) patterns), thereby enabling auto retargeting for After Develop Inspection (ADI) target generation. In the future, the framework of this composite model can be adapted to the Self-Aligned Reverse Patterning (SARP) + Cut process to address more complex MPT challenges. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

10 pages, 3164 KB

Open AccessArticle

The Influence and Compensation of Process on Measurement Accuracy in Digital Grating Focusing and Leveling Sensors

by Shiguang Li, Xianjie Li and Guocai He

Micromachines 2025, 16(12), 1326; https://doi.org/10.3390/mi16121326 - 26 Nov 2025

Viewed by 268

Abstract

The digital grating focusing and leveling sensor is a kind of wafer height sensor for focus control in a lithography tool by measuring the displacement of an optical grating image reflected from the wafer surface. The process pattern on the wafer surface can [...] Read more.

The digital grating focusing and leveling sensor is a kind of wafer height sensor for focus control in a lithography tool by measuring the displacement of an optical grating image reflected from the wafer surface. The process pattern on the wafer surface can significantly affect the measurement accuracy of the sensor. To mitigate this effect, the Criminisi algorithm for image processing is employed. First, process patterns in the optical grating image are identified and masked with a specific color—yellow in this paper. The Criminisi algorithm is then applied to recover the clear image in the masked region. To evaluate the algorithm performance, 50 masked images are recovered and compared with the original clear image where the mask ratios range from 1% to 15%. The experimental results indicate that the mean repair accuracy is below 1 nm after 10 repair iterations for a given mask ratio and the maximum error in a single repair is 68 nm across all 50 images. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

16 pages, 3257 KB

Open AccessArticle

A Two-Stage Unet Framework for Sub-Resolution Assist Feature Prediction

by Mu Lin, Le Ma, Lisong Dong and Xu Ma

Micromachines 2025, 16(11), 1301; https://doi.org/10.3390/mi16111301 - 20 Nov 2025

Viewed by 369

Abstract

Sub-resolution assist feature (SRAF) is a widely used resolution enhancement technology for improving image contrast and the common process window in advanced lithography processes. However, both model-based SRAF and rule-based SRAF methods suffer from challenges of adaptability or high computational cost. The primary [...] Read more.

Sub-resolution assist feature (SRAF) is a widely used resolution enhancement technology for improving image contrast and the common process window in advanced lithography processes. However, both model-based SRAF and rule-based SRAF methods suffer from challenges of adaptability or high computational cost. The primary learning-based SRAF method adopts an end-to-end mode, treating the entire mask pattern as a pixel map, and it is difficult to obtain precise geometric parameters for the commonly used Manhattan SRAFs. This paper proposes a two-stage Unet framework to effectively predict the centroid coordinates and dimensions of SRAF polygons. Furthermore, an adaptive hybrid attention mechanism is introduced to dynamically integrate global and local features, thus enhancing the prediction accuracy. Additionally, a warm-up cosine annealing learning rate strategy is adopted to improve the training stability and convergence speed. Simulation results demonstrate that the proposed method accurately and rapidly estimates the SRAF parameters. Compared to traditional neural networks, the proposed method can better predict SRAF patterns, with the mean pattern error and edge placement error values showing the most significant reductions. PE decreases from 25,776.44 to 15,203.33 and EPE from 5.8367 to 3.5283, respectively. This significantly improves the image fidelity of the lithography system. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

16 pages, 844 KB

Open AccessArticle

Curvilinear Sub-Resolution Assist Feature Placement Through a Data-Driven U-Net Model

by Jiale Liu, Wenjing He, Wenhao Ding, Yuhang Wang and Yijiang Shen

Micromachines 2025, 16(11), 1229; https://doi.org/10.3390/mi16111229 - 29 Oct 2025

Viewed by 539

Abstract

In advanced semiconductor manufacturing, computational lithography, particularly sub-resolution assist features (SRAFs), is crucial for enhancing the process window. However, conventional SRAF placement methodologies are hampered by a critical trade-off between speed and pattern fidelity, and they largely fail to optimize the complex, curvilinear [...] Read more.

In advanced semiconductor manufacturing, computational lithography, particularly sub-resolution assist features (SRAFs), is crucial for enhancing the process window. However, conventional SRAF placement methodologies are hampered by a critical trade-off between speed and pattern fidelity, and they largely fail to optimize the complex, curvilinear layouts essential for advanced nodes. This study develops a deep learning framework to replace and drastically accelerate the optical refinement of SRAF shapes. We established a large-scale dataset with coarse, binarized SRAF patterns as inputs. Ground-truth labels were generated via an Level-Set Method (LSM) optimized purely for optical performance. A U-Net convolutional neural network was then trained to learn the mapping from the coarse inputs to the optically optimized outputs. Experimental results demonstrate a dual benefit: the model provides a multi-order-of-magnitude acceleration over traditional CPU-based methods and is significantly faster than modern GPU-accelerated algorithms while achieving a final pattern fidelity highly comparable to the computationally expensive LSM. The U-Net-generated SRAFs exhibit high fidelity to the ground-truth layouts and comparable optical performance. Our findings demonstrate that a data-driven surrogate can serve as an effective alternative to traditional algorithms for SRAF optical refinement. This represents a promising approach to mitigating computational costs in mask synthesis and provides a solid foundation for future integrated optimization solutions. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

14 pages, 5284 KB

Open AccessArticle

Impact of Phase Defects on the Aerial Image in High NA Extreme Ultraviolet Lithography

by Kun He and Zhinan Zeng

Micromachines 2025, 16(11), 1210; https://doi.org/10.3390/mi16111210 - 24 Oct 2025

Viewed by 632

Abstract

With the development of extreme ultraviolet (EUV) lithography technology to higher numerical aperture (NA), it provides higher resolution imaging quality, which may be more sensitive to the phase defect in EUV mask. Therefore, it is necessary to comprehensively understand the effect of phase [...] Read more.

With the development of extreme ultraviolet (EUV) lithography technology to higher numerical aperture (NA), it provides higher resolution imaging quality, which may be more sensitive to the phase defect in EUV mask. Therefore, it is necessary to comprehensively understand the effect of phase defect on the imaging quality depending on the NA. We simulated aerial images of patterned EUV masks for the EUV lithography exposure tool of NA = 0.55 and NA = 0.33 using the rigorous coupled-wave analysis (RCWA) method. The results shows that higher NA enhances the contrast of aerial images, which, in turn, provides greater tolerance for phase defect. This indicates that high NA can mitigate the negative impact of phase defect on imaging quality to some extent. Furthermore, it is found that both the defect signal and the intensity loss ratio of the aerial image first increase and then decrease as the width of the phase defect increases, due to the height/width ratio of the phase defect. Meanwhile, the defect width corresponding to the maximum phase defect signal tends to become smaller as the NA becomes larger. It is also worth noting that when NA = 0.33, variations in the position of the phase defect led to fluctuations in the CD error due to the shadow effect of the absorber, while it diminishes at NA = 0.55. This is because a higher NA of 0.55 provides a stronger background field, which suppresses the shadow effect of the absorber more effectively than it does at NA = 0.33. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

17 pages, 3501 KB

Open AccessArticle

Analysis of Dynamic Stability Control of Light Source in Immersion DUV Lithography

by Yihua Zhu, Dandan Han, Chuang Wu, Sen Deng and Yayi Wei

Micromachines 2025, 16(11), 1207; https://doi.org/10.3390/mi16111207 - 23 Oct 2025

Viewed by 826

Abstract

Immersion deep ultraviolet (DUV) lithography remains an indispensable core technology in advanced integrated circuit manufacturing, particularly when combined with multiple patterning techniques to achieve sub-10 nm feature patterning. However, at advanced technology nodes, dynamic instabilities of DUV light sources—including spectral characteristics (bandwidth fluctuations, [...] Read more.

Immersion deep ultraviolet (DUV) lithography remains an indispensable core technology in advanced integrated circuit manufacturing, particularly when combined with multiple patterning techniques to achieve sub-10 nm feature patterning. However, at advanced technology nodes, dynamic instabilities of DUV light sources—including spectral characteristics (bandwidth fluctuations, and center wavelength drift), coherence variations, and pulse-to-pulse energy instability—can adversely affect imaging contrast, normalized image log-slope (NILS), and critical dimension (CD) uniformity. To quantitatively assess the impact of laser parameter fluctuations on NILS and CD, this work establishes systematic physical models for imaging perturbations caused by multi-parameter laser output instabilities under immersion DUV lithography. Through simulations, we evaluate the influence of laser parameter variations on the imaging fidelity of representative line/space (L/S) and tip-to-line (T2L) structures, thereby validating the proposed perturbation model. Research demonstrates that the spectral attributes (bandwidth fluctuation and center wavelength drift), coherence variations, and pulse energy instability collectively induce non-uniform electric field intensity distribution within photoresist, degrading NILS, and amplifying CD variation, which ultimately compromise pattern fidelity and chip yield. Notably, at advanced nodes, pulse energy fluctuation exerts a significantly greater influence on imaging errors compared to bandwidth and wavelength variations. To satisfy the 10% process window requirement for 45 nm linewidths, pulse energy fluctuations should be rigorously confined within 1%. This research provides theoretical foundations and practical insights for the design of dynamic stability control of light source and process optimization of next-generation DUV light sources. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

13 pages, 3442 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Patterning Fidelity Enhancement and Aberration Mitigation in EUV Lithography Through Source–Mask Optimization

by Qi Wang, Qiang Wu, Ying Li, Xianhe Liu and Yanli Li

Micromachines 2025, 16(10), 1166; https://doi.org/10.3390/mi16101166 - 14 Oct 2025

Cited by 1 | Viewed by 1261

Abstract

Extreme ultraviolet (EUV) lithography faces critical challenges in aberration control and patterning fidelity as technology nodes shrink below 3 nm. This work demonstrates how Source–Mask Optimization (SMO) simultaneously addresses both illumination and mask design to enhance pattern transfer accuracy and mitigate aberrations. Through [...] Read more.

Extreme ultraviolet (EUV) lithography faces critical challenges in aberration control and patterning fidelity as technology nodes shrink below 3 nm. This work demonstrates how Source–Mask Optimization (SMO) simultaneously addresses both illumination and mask design to enhance pattern transfer accuracy and mitigate aberrations. Through a comprehensive optimization framework incorporating key process metrics, including critical dimension (CD), exposure latitude (EL), and mask error factor (MEF), we achieve significant improvements in imaging quality and process window for 40 nm minimum pitch patterns, representative of 2 nm node back-end-of-line (BEOL) requirements. Our analysis reveals that intelligent SMO implementation not only enables robust patterning solutions but also compensates for inherent EUV aberrations by balancing source characteristics with mask modifications. On average, our results show a 4.02% reduction in CD uniformity variation, concurrent with a 1.48% improvement in exposure latitude and a 5.45% reduction in MEF. The proposed methodology provides actionable insights for aberration-aware SMO strategies, offering a pathway to maintain lithographic performance as feature sizes continue to scale. These results underscore SMO’s indispensable role in advancing EUV lithography capabilities for next-generation semiconductor manufacturing. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

23 pages, 2493 KB

Open AccessArticle

EAAUnet-ILT: A Lightweight and Iterative Mask Optimization Resolution with SRAF Constraint Scheme

by Ke Wang and Kun Ren

Micromachines 2025, 16(10), 1162; https://doi.org/10.3390/mi16101162 - 14 Oct 2025

Viewed by 786

Abstract

With the continuous scaling-down of integrated circuit feature sizes, inverse lithography technology (ILT), as the most groundbreaking resolution enhancement technique (RET), has become crucial in advanced semiconductor manufacturing. By directly optimizing mask patterns through inverse computation rather than rule-based local corrections, ILT can [...] Read more.

With the continuous scaling-down of integrated circuit feature sizes, inverse lithography technology (ILT), as the most groundbreaking resolution enhancement technique (RET), has become crucial in advanced semiconductor manufacturing. By directly optimizing mask patterns through inverse computation rather than rule-based local corrections, ILT can more accurately approximate target design patterns while extending the process window. However, current mainstream ILT approaches—whether machine learning-based or gradient descent-based—all face the challenge of balancing mask optimization quality and computational time. Moreover, ILT often faces a trade-off between imaging fidelity and manufacturability; fidelity-prioritized optimization leads to explosive growth in mask complexity, whereas manufacturability constraints require compromising fidelity. To address these challenges, we propose an iterative deep learning-based ILT framework incorporating a lightweight model, ghost and adaptive attention U-net (EAAUnet) to accelerate runtime and reduce computational overhead while progressively improving mask quality through multiple iterations based on the pre-trained network model. Compared to recent state-of-the-art (SOTA) ILT solutions, our approach achieves up to a 39% improvement in mask quality metrics. Additionally, we introduce a mask constraint scheme to regulate complex SRAF (sub-resolution assist feature) patterns on the mask, effectively reducing manufacturing complexity. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

12 pages, 5171 KB

Open AccessArticle

Investigation and Application of Key Alignment Parameters for Overlay Accuracy in 3D Structures

by Miao Jiang, Mingyi Yao, Ganlin Song, Yuxing Zhou, Jiani Su, Yuejing Qi and Jiangliu Shi

Micromachines 2025, 16(8), 876; https://doi.org/10.3390/mi16080876 - 29 Jul 2025

Viewed by 1500

Abstract

With the growing adoption of 3D stacked memory structures, precise alignment and overlay control have become critical for multi-layer overlay accuracy. The metrology accuracy and stability of alignment marks are crucial to ensuring optimal alignment and overlay performance. This study systematically investigates the [...] Read more.

With the growing adoption of 3D stacked memory structures, precise alignment and overlay control have become critical for multi-layer overlay accuracy. The metrology accuracy and stability of alignment marks are crucial to ensuring optimal alignment and overlay performance. This study systematically investigates the contributions of two key alignment parameters—Wafer Quality (WQ) and Alignment Position Deviation (APD)—to the alignment model residue in 3D structures. Through experimental and simulation approaches, we analyze the interplay between WQ, APD and overlay performance. Results reveal that APD exhibits a stronger correlation with uncorrectable model residue, particularly under global process variations such as etch non-uniformity. Furthermore, APD sensitivity varies directionally (X/Y direction marks) and spatially (wafer edge versus center), highlighting the need for targeted mark designs in process-sensitive zones. These findings provide actionable insights for optimizing alignment strategies, mark designs and process monitoring throughout R&D, technology development and high-volume manufacturing phases. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

15 pages, 2615 KB

Open AccessArticle

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

Cited by 1 | Viewed by 1350

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)

► Show Figures

Figure 1

15 pages, 9597 KB

Open AccessArticle

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 1117

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)

► Show Figures

Graphical abstract

18 pages, 2780 KB

Open AccessArticle

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

Cited by 2 | Viewed by 1077

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)

► Show Figures

Figure 1

10 pages, 2719 KB

Open AccessArticle

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 1244

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)

► Show Figures

Figure 1

Review

Jump to: Research

18 pages, 2718 KB

Open AccessReview

The Principle and Development of Optical Maskless Lithography Based Digital Micromirror Device (DMD)

by Xianjie Li, Guodong Cui and Guili Xu

Micromachines 2025, 16(12), 1356; https://doi.org/10.3390/mi16121356 - 29 Nov 2025

Viewed by 1167

Abstract

A comprehensive review of the DMD-based optical lithography system has been conducted. The essence of the point-array with an oblique-scanning and stepping operation principle has been systematically analyzed, which will serve as the core driving force for its development and application. Similar to [...] Read more.

A comprehensive review of the DMD-based optical lithography system has been conducted. The essence of the point-array with an oblique-scanning and stepping operation principle has been systematically analyzed, which will serve as the core driving force for its development and application. Similar to conventional lithography, the system development has been presented from the aspects of critical dimension (CD) resolution, overlay accuracy, and throughput. With the unique characterizations of the digital virtue mask, achievements are summarized from integrated circuit (IC) manufacturing to various micro-scale fabrication processes. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

28 pages, 4300 KB

Open AccessReview

Thermal Control Systems in Projection Lithography Tools: A Comprehensive Review

by Di Cao, He Dong, Zhibo Zeng, Wei Zhang, Xiaoping Li and Hangcheng Yu

Micromachines 2025, 16(8), 880; https://doi.org/10.3390/mi16080880 - 29 Jul 2025

Cited by 4 | Viewed by 3658

Abstract

This review examines the design of thermal control systems for state-of-the-art deep ultraviolet (DUV) and extreme ultraviolet (EUV) projection lithography tools. The lithographic system under investigation integrates several critical subsystems along the optical transmission chain, including the light source, reticle stage, projection optics [...] Read more.

This review examines the design of thermal control systems for state-of-the-art deep ultraviolet (DUV) and extreme ultraviolet (EUV) projection lithography tools. The lithographic system under investigation integrates several critical subsystems along the optical transmission chain, including the light source, reticle stage, projection optics (featuring DUV refractive lenses and EUV multilayer mirrors), immersion liquid, wafer stage, and metrology systems. Under high-power irradiation conditions with concurrent thermal perturbations, the degradation of thermal stability and gradient uniformity within these subsystems significantly compromises exposure precision. Through a systematic analysis of the thermal challenges specific to each subsystem, this review synthesizes established thermal control systems across two technical dimensions: thermal control structures and thermal control algorithms. Prospects for future advancements in lithographic thermal control are also discussed. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

25 pages, 2727 KB

Open AccessReview

AI-Powered Next-Generation Technology for Semiconductor Optical Metrology: A Review

by Weiwang Xu, Houdao Zhang, Lingjing Ji and Zhongyu Li

Micromachines 2025, 16(8), 838; https://doi.org/10.3390/mi16080838 - 22 Jul 2025

Cited by 2 | Viewed by 3347

Abstract

As semiconductor manufacturing advances into the angstrom-scale era characterized by three-dimensional integration, conventional metrology technologies face fundamental limitations regarding accuracy, speed, and non-destructiveness. Although optical spectroscopy has emerged as a prominent research focus, its application in complex manufacturing scenarios continues to confront significant [...] Read more.

As semiconductor manufacturing advances into the angstrom-scale era characterized by three-dimensional integration, conventional metrology technologies face fundamental limitations regarding accuracy, speed, and non-destructiveness. Although optical spectroscopy has emerged as a prominent research focus, its application in complex manufacturing scenarios continues to confront significant technical barriers. This review establishes three concrete objectives: To categorize AI–optical spectroscopy integration paradigms spanning forward surrogate modeling, inverse prediction, physics-informed neural networks (PINNs), and multi-level architectures; to benchmark their efficacy against critical industrial metrology challenges including tool-to-tool (T2T) matching and high-aspect-ratio (HAR) structure characterization; and to identify unresolved bottlenecks for guiding next-generation intelligent semiconductor metrology. By categorically elaborating on the innovative applications of AI algorithms—such as forward surrogate models, inverse modeling techniques, physics-informed neural networks (PINNs), and multi-level network architectures—in optical spectroscopy, this work methodically assesses the implementation efficacy and limitations of each technical pathway. Through actual application case studies involving J-profiler software 5.0 and associated algorithms, this review validates the significant efficacy of AI technologies in addressing critical industrial challenges, including tool-to-tool (T2T) matching. The research demonstrates that the fusion of AI and optical spectroscopy delivers technological breakthroughs for semiconductor metrology; however, persistent challenges remain concerning data veracity, insufficient datasets, and cross-scale compatibility. Future research should prioritize enhancing model generalization capability, optimizing data acquisition and utilization strategies, and balancing algorithm real-time performance with accuracy, thereby catalyzing the transformation of semiconductor manufacturing towards an intelligence-driven advanced metrology paradigm. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

19 pages, 1911 KB

Open AccessReview

Review of Directed Self-Assembly Material, Processing, and Application in Advanced Lithography and Patterning

by Xiuyan Cheng, Di Liang, Miao Jiang, Yufei Sha, Xiaonan Liu, Jinlai Liu, Qingchen Cao and Jiangliu Shi

Micromachines 2025, 16(6), 667; https://doi.org/10.3390/mi16060667 - 31 May 2025

Cited by 1 | Viewed by 5031

Abstract

Directed self-assembly (DSA) lithography, a cutting-edge technology based on the self-assembly of block copolymers (BCPs), has received significant attention in recent years. Combining DSA with established lithography technologies, such as extreme ultraviolet (EUV), deep ultraviolet (DUV), electron beam lithography, and nanoimprint lithography, significantly [...] Read more.

Directed self-assembly (DSA) lithography, a cutting-edge technology based on the self-assembly of block copolymers (BCPs), has received significant attention in recent years. Combining DSA with established lithography technologies, such as extreme ultraviolet (EUV), deep ultraviolet (DUV), electron beam lithography, and nanoimprint lithography, significantly enhances the resolution of target patterns and device density. Currently, there are two commonly used methods in DSA: graphoepitaxy, employing lithographically defined topographic templates to guide BCP assembly, and chemoepitaxy, utilizing chemically patterned surfaces with precisely controlled interfacial energies to direct nanoscale phase segregation. Through novel DSA lithography technology, nanoscale patterns with smaller feature sizes and higher densities can be obtained, realizing the miniaturization of hole and line patterns and pitch multiplication and improving the roughness and local critical dimension uniformity (LCDU). It is gradually becoming one of the most promising and advanced lithography techniques. DSA lithography technology has been applied in logic, memory, and optoelectronic device fabrications. Full article

(This article belongs to the Special Issue Recent Advances in Lithography)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Recent Advances in Lithography

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (18 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI