IEEE Transactions on Semiconductor Manufacturing最新文献_第4页

In-Situ Plasma Monitoring Using Multiple Plasma Information in SiO₂ Etch Process sio2蚀刻过程中多等离子体信息的原位等离子体监测

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-04-09 DOI: 10.1109/TSM.2025.3559301

Min Ho Kim;Jeong Eun Jeon;Sang Jeen Hong

{"title":"In-Situ Plasma Monitoring Using Multiple Plasma Information in SiO₂ Etch Process","authors":"Min Ho Kim;Jeong Eun Jeon;Sang Jeen Hong","doi":"10.1109/TSM.2025.3559301","DOIUrl":"https://doi.org/10.1109/TSM.2025.3559301","url":null,"abstract":"Optical emission spectroscopy (OES) data analysis with inert gas, called rare gas tracing method, has become a widely accepted method for the monitoring of plasma process. However, it is becoming less desirable due to the need for a higher hardmask selectivity in etch. Conventional OES analysis focuses on bulk plasma properties, such as electron temperature and density, but fail to capture the full complexity of etch rate changes influenced by both ohmic heating and ion acceleration. To address these limitations, we propose an alternative approach that incorporates multiple plasma information (PI), offering a more comprehensive view of plasma mechanisms. This new framework was applied to develop an OES-based monitoring technique without inert gases. By modulating source and bias powers to vary both ohmic heating and ion acceleration, the multiple PI model demonstrated a higher <inline-formula> <tex-math>$R^{2}$ </tex-math></inline-formula> score (~0.97) compared to the traditional Ar-based PI model (~0.8). In addition, explainable artificial intelligence (XAI) indicated that multiple PI had greater importance, demonstrating its effectiveness in monitoring etch rates in non-inert gas processes. It not only detects changes in the etch process, but also identifies whether the variations stem from chemical or physical reactions to be useful for advanced process control.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 3","pages":"543-553"},"PeriodicalIF":2.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling and Designing a GaN-Growth Reactor With Halogen-Free Vapor Phase Epitaxy: NH3 Decomposition at the Catalytic Surface of Components to Replicate Parasitic Polycrystal Formation 无卤气相外延氮化镓生长反应器的建模与设计：组件催化表面NH3分解以复制寄生多晶形成

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-04-07 DOI: 10.1109/TSM.2025.3558328

Hiroki Shimazu;Shin-Ichi Nishizawa;Shugo Nitta;Hiroshi Amano;Daisuke Nakamura

{"title":"Modeling and Designing a GaN-Growth Reactor With Halogen-Free Vapor Phase Epitaxy: NH3 Decomposition at the Catalytic Surface of Components to Replicate Parasitic Polycrystal Formation","authors":"Hiroki Shimazu;Shin-Ichi Nishizawa;Shugo Nitta;Hiroshi Amano;Daisuke Nakamura","doi":"10.1109/TSM.2025.3558328","DOIUrl":"https://doi.org/10.1109/TSM.2025.3558328","url":null,"abstract":"Achieving long-duration, large bulk GaN growth is crucial to supply low-cost, high-quality GaN. Halogen-free vapor phase epitaxy (HF-VPE) is a promising method for bulk GaN growth but faces challenges due to severe polycrystals deposition on reactor components, such as the source-gas nozzles, which impedes stable, extended growth. In this study, we developed models to simulate the polycrystal deposition in HF-VPE-GaN growth conditions by including surface reactions of GaN formation and NH3 decomposition. Moreover, we devised conditions for controlling gas flow and interdiffusion to suppress polycrystal deposition around the source-gas nozzles. Experimental results aligned with simulations, showing that increasing the distance between Ga and NH3 nozzles and replacing the sheath gas from H2 to N2 effectively minimized polycrystal formation. The findings confirm that reducing NH3 concentration through catalytic surface decomposition on refractory components is crucial to polycrystal suppression. Optimizing nozzle dimensions and gas species synergistically controls the gas flow and interdiffusion. The constructed models contribute to advancing the design of polycrystal suppressive structures and conditions for long-duration bulk GaN growth.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 2","pages":"311-323"},"PeriodicalIF":2.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VECSNet: A Nondestructive Automatic VCSEL Chip Detection Network With Pixelwise Segmentation 基于像素分割的VCSEL芯片无损自动检测网络

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-04-04 DOI: 10.1109/TSM.2025.3558015

Shuai Guo;Dengao Li;Jumin Zhao;Shuang Qiu;Bao Tang;Biao Luo

{"title":"VECSNet: A Nondestructive Automatic VCSEL Chip Detection Network With Pixelwise Segmentation","authors":"Shuai Guo;Dengao Li;Jumin Zhao;Shuang Qiu;Bao Tang;Biao Luo","doi":"10.1109/TSM.2025.3558015","DOIUrl":"https://doi.org/10.1109/TSM.2025.3558015","url":null,"abstract":"Dark line defects (DLDs) are critical factors that significantly limit the performance of vertical-cavity surface-emitting lasers (VCSELs). Recently, convolutional neural network (CNN)-based methods have shown strong feature extraction capabilities, achieving exceptional performance across various fields. However, these methods still face limitations on the segmentation samples with weak texture, varying shapes and blurred boundary information. To overcome these limitations, a novel segmentation method named VECSNet is proposed in this work. Electroluminescence imaging technology is employed to capture the emission characteristics of VCSELs and develop the corresponding dataset. To improve the extraction of emission features, a parallel dual-encoding structure is designed to capture both spatial and semantic information. Additionally, a feature fusion attention (FFA) block is introduced to effectively fuse features extracted from different branches. Faced with blurred boundary information, a boundary detector is proposed to guide each fusion connection in acquiring boundary feature information and enrich feature representation. Furthermore, to improve segmentation precision for areas with varying shapes, auxiliary logits are introduced to enhance discriminative ability of the network from multiple levels. Experimental results on the VCSEL emission segmentation dataset demonstrate that the proposed method achieves a high Dice score (92.5%) with fewer parameters (6.4M), outperforming other state-of-the-art segmentation approaches.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 2","pages":"270-280"},"PeriodicalIF":2.3,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mechanistic Analysis of the Effect of Gap on Convex Curves of Wafer in Double-Sided Polishing 双面抛光中间隙对晶圆凸曲线影响的机理分析

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-03-28 DOI: 10.1109/TSM.2025.3574490

Jiayu Chen;Yiran Liu;Xiangang Wang;Jun Cao;Wenjie Yu;Lei Zhu

引用次数: 0

A Proactive Approach of Optimizing Real-Time Equipment Monitoring Settings for Enhancing End-of-Line Yield 一种优化实时设备监控设置以提高产率的主动方法

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-03-27 DOI: 10.1109/TSM.2025.3574015

Kuan-Chun Lin;Shi-Chung Chang;Yu-Chi Liao;Cheng-Wei Wu

{"title":"A Proactive Approach of Optimizing Real-Time Equipment Monitoring Settings for Enhancing End-of-Line Yield","authors":"Kuan-Chun Lin;Shi-Chung Chang;Yu-Chi Liao;Cheng-Wei Wu","doi":"10.1109/TSM.2025.3574015","DOIUrl":"https://doi.org/10.1109/TSM.2025.3574015","url":null,"abstract":"In semiconductor manufacturing, wafer acceptance test (WAT) data consists of end-of-line (EOL) electrical parameters reflecting product quality and process capability, while in-line equipment plays a crucial role in shaping these outcomes. Engineers collect real-time monitoring (RTM) data that are used for reactive diagnosis when WAT detects issues. It is highly desirable to have quantitative prediction models linking RTM data to EOL parameters, so that RTM control region settings can be proactively optimized to keep WAT results on target with low variations, ultimately enhancing EOL yield. This paper designs WAPOR, a framework for EOL parameter prediction exploiting significant RTM items and their monitoring setting optimization, to proactively reduce resultant WAT variations. There are three innovations: (i) Key RTM Item Identification (H-RIS) for individual EOL parameters by combining three machine learning methods for both linear and non-linear analysis; (ii) WAT Parameter Prediction Model (WPBM) learned from applying Deep Back-Propagation Neural Networks (DBPN) to multi-dimensional, non-linear prediction of an EOL parameter value based on its key RTM items; and (iii) equipment monitoring control setting optimization (RRS-GA) to make WAT on target with low variation. As such, WAPOR moves beyond traditional linear approaches, uncovers complex relationships and empowers engineers to set RTM parameters proactively to make WAT forecast fall within WAT specification and minimize its variance. Simulation results demonstrate that WAPOR maintains WAT target alignment within 2% of the target while reducing variation by 49%. WAPOR has a good potential to improve process capability and EOL yield.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 3","pages":"469-477"},"PeriodicalIF":2.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Diffusion-Model-Based Methodology for Virtual Silicon Data Generation 基于扩散模型的虚拟硅数据生成方法

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-03-26 DOI: 10.1109/TSM.2025.3554685

Liang-Yu Chen;Michael Kao;Shih-Hao Chen;Chia-Hsiang Yang

{"title":"A Diffusion-Model-Based Methodology for Virtual Silicon Data Generation","authors":"Liang-Yu Chen;Michael Kao;Shih-Hao Chen;Chia-Hsiang Yang","doi":"10.1109/TSM.2025.3554685","DOIUrl":"https://doi.org/10.1109/TSM.2025.3554685","url":null,"abstract":"Silicon data allow designers to enhance the chip performance by leveraging machine learning techniques. By gaining a deeper understanding of the distributions of interested features within a wafer, designers can predict chip behaviors more accurately. However, real silicon data may not always be available. This work presents a methodology for generating high-quality synthetic silicon data and verifies its effectiveness through several metrics. Silicon features obtained by chip probing (CP) and wafer acceptance test (WAT) are combined to create more comprehensive data, enabling to conduct design-technology co-optimization (DTCO). Unlike the generative adversarial network (GAN) based methodology used in prior work, this work utilizes a diffusion model to generate synthetic silicon data. The Jensen-Shannon (JS) divergence similarity and Frechet Inception Distance (FID) are used to evaluate the distribution and to quantify the quality of synthetic data, respectively. Experimental results demonstrate that the diffusion model is able to extract the multi-feature silicon data distribution more accurately, with an average JS divergence similarity of 0.987 and an FID of 6.28. This methodology enables to generate a substantial volume of silicon samples for extensive silicon data analysis and DTCO acceleration.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 2","pages":"146-153"},"PeriodicalIF":2.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantifying the Impact of Outdoor Airborne Nano-Contamination on eSiGe Defect Generation and Machine Learning-Based Predictive Modeling 室外空气纳米污染对eSiGe缺陷产生的量化影响及基于机器学习的预测建模

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-03-26 DOI: 10.1109/TSM.2025.3554783

Jongmin Lee;Jungtae Park;Il-Jin Kim;Haeun Lee;Sehoon Park

{"title":"Quantifying the Impact of Outdoor Airborne Nano-Contamination on eSiGe Defect Generation and Machine Learning-Based Predictive Modeling","authors":"Jongmin Lee;Jungtae Park;Il-Jin Kim;Haeun Lee;Sehoon Park","doi":"10.1109/TSM.2025.3554783","DOIUrl":"https://doi.org/10.1109/TSM.2025.3554783","url":null,"abstract":"A thorough investigation was conducted to determine the impact of outdoor airborne nanoparticles on defect generation during semiconductor manufacturing. Periods of elevated airborne particle levels, along with increased occurrences of embedded Silicon-Germanium (eSiGe) defects, were analyzed using experimental bare wafers designed to capture nanoparticles. Defect counts were analyzed to trace their origins. A novel data processing algorithm was developed to clarify and quantify the relationship between external airborne nanoparticles and defect formation. The findings indicate that eSiGe defect particles attributable to external airborne nano-contamination were generated at rates ranging from 1% to 6%, depending on the fab site. The robustness of the algorithm was validated through the application of an Artificial Neural Network (ANN) technique. Key parameters influencing eSiGe defects, identified as outdoor PM2.5 and Fab particles, were further analyzed using Random Forest Regression (RFG) and Quantile Regression (QR). Additionally, the application of Support Vector Regression (SVR) significantly enhanced the prediction accuracy of eSiGe defect particles, achieving an improvement of approximately 56% compared to RFG modeling. This study uniquely combines short-term experimental methods with long-term inline data science techniques to elucidate the effects of outdoor nanoparticles on eSiGe defects.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 2","pages":"178-184"},"PeriodicalIF":2.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation and Experimental Analysis of Contactless Chip Pickup Process Based on a Vortex Flow Gripper 基于涡流抓取器的非接触式芯片拾取过程仿真与实验分析

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-03-24 DOI: 10.1109/TSM.2025.3553559

Peiran Zhai;Zhoulong Xu;Zhouping Yin;Xiaohang Li;Bin Xie;Hao Wu

{"title":"Simulation and Experimental Analysis of Contactless Chip Pickup Process Based on a Vortex Flow Gripper","authors":"Peiran Zhai;Zhoulong Xu;Zhouping Yin;Xiaohang Li;Bin Xie;Hao Wu","doi":"10.1109/TSM.2025.3553559","DOIUrl":"https://doi.org/10.1109/TSM.2025.3553559","url":null,"abstract":"As the preceding process of chip-to-wafer (C2W) hybrid bonding, die pick-up, and transfer are critical in 3D heterogeneous integration (3D HI) technique. Especially, with the ever-shrinking die thickness and ever-increasing bumps on the die surface, mechanical scratches and electrostatic interference on chips caused by the traditional contact-type pickup process cannot be tolerated. Therefore, it is the trend to implement contactless pickup head to realize damage-free chip transfer. Herein, a contactless, pneumatic pickup head based on vortex flow was designed for the efficient and contactless grab of <inline-formula> <tex-math>$50~mu $ </tex-math></inline-formula>m ultrathin chips. A baffle structure on the four corners of pickup head was designed, which can achieve stable noncontact pickup of target chip and maintain the position under multiangle loading conditions. Furthermore, we optimized baffle structure to reduce the oscillation of the chip by more than 50%. We explored the underlying mechanism of pneumatic noncontact pickup through computational fluid dynamics (CFD) simulation by three turbulence models. Further, a high-precision vortex platform was built to investigate the pickup force characteristics, radial pressure distribution, and oscillations for different intake pressure and their influence on the noncontact pickup effect. Eventually, the simulation and experimental results indicate that the optimal intake pressure for stable non-contact pickup is between 20 and 30 kPa. This study provides design and optimization methods for stable noncontact picking of microchips, offering theoretical and experimental basis for selecting the optimal air intake pressure in practical applications.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 2","pages":"324-331"},"PeriodicalIF":2.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study on Particle Emission Efficiency of a Plasma Enhanced Chemical Vapor Deposition Chamber During Periodic Cycle Purge Process Using an Improved Single Particle Light Scattering Method 利用改进的单粒子光散射法研究等离子体增强化学气相沉积腔在周期性吹扫过程中的粒子发射效率

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-03-21 DOI: 10.1109/TSM.2025.3572028

Myungjoon Kim;Minwoo Jang;Minchul Jung;Hyungsun Han;Suyeon Jung;Yoonbeom Song;Youngsoo Jung;Dohyung Kim;Jihun Mun;Byeonghyeon Min;Seunghyon Kang;Eunyoung Han;Myeonghun Oh;Young Jeong Kim

引用次数: 0

Effects of the Applied Power of Remote Plasma System With Green Alternative Chamber Cleaning Gas of Carbonyl Fluoride 氟羰基清洁气对远程等离子体系统应用功率的影响

IF 2.3 3区工程技术

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-03-21 DOI: 10.1109/TSM.2025.3572285

Se Yun Jo;Ah Hyun Park;Sang Jeen Hong

{"title":"Effects of the Applied Power of Remote Plasma System With Green Alternative Chamber Cleaning Gas of Carbonyl Fluoride","authors":"Se Yun Jo;Ah Hyun Park;Sang Jeen Hong","doi":"10.1109/TSM.2025.3572285","DOIUrl":"https://doi.org/10.1109/TSM.2025.3572285","url":null,"abstract":"An effort to find an alternative dry-cleaning process gas with low global warming potential (GWP) has been conducted to decrease greenhouse gas emissions. Carbonyl fluoride (COF2) is one of the candidates as an alternative gas for plasma-enhanced chemical vapor deposition (PECVD) chamber cleaning because of its lower GWP compared to the currently employed <inline-formula> <tex-math>$mathrm {NF}_{mathrm {3}}$ </tex-math></inline-formula> gas. The dry-cleaning process conditions containing the power amount of the plasma source is related to the dissociation rate of the cleaning gas and dry-cleaning performance. We investigated the effects of the amount of remote plasma power to the chamber cleaning rate with COF2, and its effects with diluted gases of <inline-formula> <tex-math>$mathrm {O}_{mathrm {2}}$ </tex-math></inline-formula> and Ar. By the comparison of both numerical analysis and experiment, we found that the change of the amount of power induced different production rates of species in the gas mixture. In the case of <inline-formula> <tex-math>$mathrm {O}_{mathrm {2}}$ </tex-math></inline-formula> dilution, oxygen radicals prevail in the plasma, and it produces stable by-product of <inline-formula> <tex-math>$mathrm {CO}_{mathrm {2}}$ </tex-math></inline-formula> with the reaction of oxygen radicals to yield more fluorine atoms and radicals. We conclude that oxygen radicals have a significant role in the dissociation of the COF2, production of fluorine radicals, and it helps to reduce the amount of cleaning inhibitors such as C-C and C-F compounds. Additional dilution gases for cleaning gas affect production mechanisms and rates of species.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"38 3","pages":"624-633"},"PeriodicalIF":2.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0