2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)最新文献_第2页

Real-Time Automated Socket Inspection using Advanced Computer Vision and Machine Learning : DI: Defect Inspection and Reduction 使用先进计算机视觉和机器学习的实时自动插座检测:DI:缺陷检测和减少

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792494

C. Edwards, Aditya Kumar, Alex Vaske, Nathan McDaniel, Dipali Pradhan, Debashis Panda

引用次数: 1

Negative Mode E-Beam Inspection of the Contact Layer 接触层负模电子束检测

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792528

O. Patterson, MD Golam Faruk, Datong Zhang, Guanchen He, B. Sheumaker

引用次数: 1

On Updating a Virtual Metrology Model in Semiconductor Manufacturing via Transfer Learning 基于迁移学习的半导体制造虚拟计量模型更新研究

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792514

Rebecca Clain, Ikram Azzizi, Valeria Borodin, A. Roussy

引用次数: 0

Robust Process Development for Dislocation Free DTI Formation 无位错DTI形成的稳健工艺开发

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792532

Qiong Luo, Huang Jing Yan, Zhou Jianbo, Ong Shiang Yang

引用次数: 0

Wafer Geometry Technique for Blank 300mm Silicon Wafers 空白300mm硅片的晶圆几何技术

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792490

J. Trujillo-Sevilla, A. Roqué-Velasco, Miguel Jesús Sicilia, Ó. Casanova-González, José Manuel Ramos-Rodríguez, J. Gaudestad

引用次数: 1

Nano Filtration Using Polysulfone Membrane : CFM: Contamination Free Manufacturing 采用聚砜膜的纳米过滤:CFM:无污染制造

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792533

J. Tan, R. Shick, Joseph A. Peri, I-fan Wang, Amarnauth Singh, R. Beera

{"title":"Nano Filtration Using Polysulfone Membrane : CFM: Contamination Free Manufacturing","authors":"J. Tan, R. Shick, Joseph A. Peri, I-fan Wang, Amarnauth Singh, R. Beera","doi":"10.1109/asmc54647.2022.9792533","DOIUrl":"https://doi.org/10.1109/asmc54647.2022.9792533","url":null,"abstract":"Defect control is imperative to leading-edge semiconductor industry. Nano filtration has been effective at reducing defects caused by particles and metal contamination. In this presentation, we focus on filters that consist of polysulfone (PSF) membrane and ion exchange membrane (IEM) for effective removal of particles and metal ions. In the real application case, either one filter containing dual layer membranes (PSF + IEM) or two separate filters (PSF filter + IEM filter) can be installed to remove both particles and metal ions from chemicals or water used in semiconductor manufacturing, depending on the process conditions and requirements. Polysulfone polymer membrane has a highly asymmetric structure that allows superior flow rate and fine particle retention. With optimal filter design, the best filters can remove particles down to 1 nm size while exhibiting a low pressure drop. The membrane in IEM typically has negatively charged functional groups on the surface. The leading IEM product can effectively remove >90% trace metal ions from solutions. This manuscript will give an overview of the issues at end users and discuss how advanced filtration technology help solve the issues and enable semiconductor manufacturing.","PeriodicalId":436890,"journal":{"name":"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116038705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In-situ Cleaning of Post-etch Byproducts by Manipulating Dechucking Environment Gas in Silicon Etch Process 利用脱哈克环境气体对硅蚀刻过程中蚀刻后副产物的原位清洗

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792508

Ki Dong Yang, Hanbit Park, Joonho Lee, E. Hwang, Jiwoo Jeong, S. Kwon, Kihyun Kim, Jaein Jeong, Eunyoung Han, Young Jeong Kim, Joong Jung Kim

{"title":"In-situ Cleaning of Post-etch Byproducts by Manipulating Dechucking Environment Gas in Silicon Etch Process","authors":"Ki Dong Yang, Hanbit Park, Joonho Lee, E. Hwang, Jiwoo Jeong, S. Kwon, Kihyun Kim, Jaein Jeong, Eunyoung Han, Young Jeong Kim, Joong Jung Kim","doi":"10.1109/asmc54647.2022.9792508","DOIUrl":"https://doi.org/10.1109/asmc54647.2022.9792508","url":null,"abstract":"In this work, the ability to remove post-etch residues by simply changing dechucking environment gas from Ar to O2 is presented. The O2 dechucking process was observed to enhance in-situ cleaning effect, reducing Cl and Br anion by 93% and 50%, respectively, on the wafer surface (HPIC) and 101 ~ 102 times within the Si substrate (tof-SIMS). FOUP ion analysis and optical emission spectroscopy results also revealed that the amount of process outgas can be significantly reduced. As the halogen atoms that are originally remaining inside the Si substrate was removed, the damaged Si layer was also reduced by O2 curing. By this simple method, within the etch process, the wafer can be patterned and additionally, in-situ cleaned. Furthermore, based on DFT calculation, we clarified that O radicals can remove polymeric residues like SiOxCly and SiOxBry by replacing halogen atoms on energy perspective. The O2 treated oxide has less number of interface trap (Nit), proving device performance also can be enhanced.","PeriodicalId":436890,"journal":{"name":"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"2000 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116680570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

On an Application of Denoising to the Uncertainty Quantification of Line Edge Roughness Estimation 去噪在线边缘粗糙度估计不确定性量化中的应用

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792521

Inimfon I. Akpabio, S. Savari

引用次数: 2

Feature Selection for Virtual Metrology Modeling: An application to Chemical Mechanical Polishing 虚拟计量建模的特征选择:在化学机械抛光中的应用

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792527

Oussama Djedidi, Rebecca Clain, Valeria Borodin, A. Roussy

{"title":"Feature Selection for Virtual Metrology Modeling: An application to Chemical Mechanical Polishing","authors":"Oussama Djedidi, Rebecca Clain, Valeria Borodin, A. Roussy","doi":"10.1109/asmc54647.2022.9792527","DOIUrl":"https://doi.org/10.1109/asmc54647.2022.9792527","url":null,"abstract":"This paper focuses on the feature selection problem in a virtual metrology task applied to a chemical mechanical polishing process. One of the main challenges specific to virtual metrology modeling is the relatively wide availability of measurements and traces (features) versus the scarcity of samples (entries), as they are usually costly to obtain. To overcome these challenges, we propose a hybrid feature selection algorithm, called Enhanced Hybrid Feature Selection (EHFS), that combines a filter approach and a genetic algorithm embedding a machine learning model. The filter starts by eliminating noisy and uninformative features. Then, in the wrapper stage, the genetic algorithm is augmented by a solution archive to favor exploration. This added feature avoids the reevaluation of duplicate candidate solutions and consequently decreases the computational time of EHFS.Numerical experiments, conducted on industrial and benchmark datasets, show that the proposed solution approach performs competitively in terms of both solution quality and computational time compared with two existing approaches: the general-purpose Forward Feature Selection (FFS) and virtual metrology-specific Evolutionary Repetitive Backward Elimination (ERBE).","PeriodicalId":436890,"journal":{"name":"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122135581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D NAND vertical channel defect inspection and classification solution on a DL-based e-beam system : DI : Defect Inspection and Reduction 基于dl的电子束系统的三维NAND垂直通道缺陷检测和分类解决方案:DI:缺陷检测和减少

2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2022-05-02 DOI: 10.1109/asmc54647.2022.9792511

Cheng Hung Wu, Yen-Chun Chuan Sun, Rishabh Kushwaha, Piyush Bajpai, Shao Chang Cheng

{"title":"3D NAND vertical channel defect inspection and classification solution on a DL-based e-beam system : DI : Defect Inspection and Reduction","authors":"Cheng Hung Wu, Yen-Chun Chuan Sun, Rishabh Kushwaha, Piyush Bajpai, Shao Chang Cheng","doi":"10.1109/asmc54647.2022.9792511","DOIUrl":"https://doi.org/10.1109/asmc54647.2022.9792511","url":null,"abstract":"With data storage capacity increasing, more memory cell stacks for three-dimensional NAND (3D NAND) devices are developed. When stacking more thin-film layers, the capability to form uniform high aspect ratio (HAR) structures becomes a key 3D NAND process step. Therefore, in 3D NAND manufacturing, etch process control is especially important. Etch processes generate HAR structures and defects are usually buried in the deep trenches or holes, which become inspection challenges. Defect control is important for semiconductor manufacturing to ensure device quality. In this study, a high landing energy (HiLE) e-beam defect inspection system with a wide landing energy operation range is utilized to compare scanning electron microscopy (SEM) images of different landing energy to get the best signal for defects of interest (DOI) that are buried in the deep vertical channel (VC) holes. A landing energy of 30KeV was determined to provide best DOI imaging. In addition, to reduce the burden of manual defect classification (MDC) and improve traditional algorithm limitations, a deep learning (DL)-based algorithm methodology is implemented that successfully demonstrates detection of DOI at ~6 μm depth within the VC holes of a 96-layer 3D NAND device, while also achieving auto defect classification (ADC) with >90% purity by each VC row.","PeriodicalId":436890,"journal":{"name":"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128179896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1