2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)最新文献_第6页

A novel approach to tool monitoring for furnace tools with dynamic recipe management 基于动态配方管理的炉具监控新方法

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373205

Shiladitya Chakravorty, Chihyun Jung, Garrett Szafman, J. Rajachidambaram, Bradley Savoy, Satyajit Shinde

引用次数: 4

Modelling pattern dependent variations in semi-additive copper electrochemical plating: AP/DFM: Advanced patterning / design for manufacturability 模拟模式依赖于半添加剂铜电化学镀的变化:AP/DFM:可制造性的高级模式/设计

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373169

C. Lang, D. Boning

引用次数: 2

Airborne molecular contamination: Formation, impact, measurement and removal of nitrous acid (HNO2) 空气分子污染:亚硝酸(HNO2)的形成、影响、测量和去除

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373195

J. Lobert, Reena Srivastava, F. Belanger

{"title":"Airborne molecular contamination: Formation, impact, measurement and removal of nitrous acid (HNO2)","authors":"J. Lobert, Reena Srivastava, F. Belanger","doi":"10.1109/ASMC.2018.8373195","DOIUrl":"https://doi.org/10.1109/ASMC.2018.8373195","url":null,"abstract":"Airborne molecular contamination (AMC) is a significant contributor to the loss of yield in semiconductor processes [1–4]. Impact of weak acids has only been considered for process technologies of 22 nm and below [5–8]. One such weak acid is nitrous acid (HNO2 or HONO), which has no demonstrated direct impact on processes or equipment, but has nevertheless been a target for removal by AMC filtration. HNO2 is commonly formed on all surfaces in all environments from NO2 gas, one of the main oxides of nitrogen formed from combustion processes and ambient air photochemistry. This study investigated the behavior of the NOX/HNOx system around typical AMC filter adsorbents. We find that NO gas passes through AMC filters unchanged, whereas NO2 is converted mostly to NO, but also to HNO2 at the low ppb level, increasing AMC load downstream of filters. Various adsorbents can capture HNO2, but filter lifetimes are short due to the release of the volatile compound over time. The recommendation is to critically evaluate the impact of HNO2 on processes and equipment and adjust AMC filtration needs accordingly.","PeriodicalId":349004,"journal":{"name":"2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124362387","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: 4

Gas cluster ion beam processing for improved self aligned contact yield at 7 nm node FinFET: MJ: MOL and junction interfaces 气簇离子束处理提高7nm节点FinFET: MJ: MOL和结界面的自对准接触良率

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373209

S. Fan, S. Teehan, K. Chung, Alex Varghese, Mark Lenhardt, P. Montanini, S. Skordas, B. Haran, S. Tsai, R. Xie

{"title":"Gas cluster ion beam processing for improved self aligned contact yield at 7 nm node FinFET: MJ: MOL and junction interfaces","authors":"S. Fan, S. Teehan, K. Chung, Alex Varghese, Mark Lenhardt, P. Montanini, S. Skordas, B. Haran, S. Tsai, R. Xie","doi":"10.1109/ASMC.2018.8373209","DOIUrl":"https://doi.org/10.1109/ASMC.2018.8373209","url":null,"abstract":"Self-aligned contact (SAC) is required for 7 nm node to reduce susceptibility of contact-to-gate short failures. This requires forming a SAC cap on metal-recessed gate. The SAC cap formation is usually achieved by removing nitride on the field by planarization techniques such CMP (chemical mechanical polishing) or GCIB (gas cluster ion beam) processes. Significant gate stack height variation can be observed lot-to-lot and wafer-to-wafer due to accumulated variations from multiple steps, including several CMP steps, before the SAC cap module, especially during early research and development prior to full optimization of the steps before the SAC cap module. GCIB potentially offers a method by which the early development stage variation due to CMP steps can be reduced, allowing integration and device learning during the early stages of a program. This study shows a comparison of SAC cap formation by CMP only vs. GCIB with integrated metrology enabled location specific processing. By using GCIB with feed-forward scatterometry measurements taken from a 2D measurement pad we have been able to significantly improve both lot-to-lot and wafer-to-wafer variation on early development wafers. This has led to improvement in within wafer SAC cap thickness non-uniformity, wafer to wafer and lot to lot device yield for gate-contact over a CMP-only process flow.","PeriodicalId":349004,"journal":{"name":"2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131226148","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

Design based automatic defect classification at advanced technology nodes: DI: Defect inspection and reduction 基于先进技术节点缺陷自动分类的设计:DI:缺陷检测和减少

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373179

Jay K Shah, Abhinav Jain, F. Levitov, Shay Yasharzade, J. G. Sheridan, Vu Nguyen, Hoang Nguyen

引用次数: 3

Advanced run-to-run controller in semiconductor manufacturing with real-time equipment condition: APC: Advanced process control; AM: Advanced metrology 具有实时设备条件的半导体制造中先进的运行-运行控制器:APC:先进的过程控制;高级计量学

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373161

Wei-Ting Yang, J. Blue, A. Roussy, M. Reis, J. Pinaton

{"title":"Advanced run-to-run controller in semiconductor manufacturing with real-time equipment condition: APC: Advanced process control; AM: Advanced metrology","authors":"Wei-Ting Yang, J. Blue, A. Roussy, M. Reis, J. Pinaton","doi":"10.1109/ASMC.2018.8373161","DOIUrl":"https://doi.org/10.1109/ASMC.2018.8373161","url":null,"abstract":"Run-to-Run (R2R) control has become a common process regulating approach in the semiconductor industry. Conventionally, key process parameters are regulated with respect to the measured metrology data. However, wafer quality can be affected by complex factors related to equipment condition. The steady progress of information technologies enable us to collect and handle larger amounts of data, open new perspectives to explore the interactions between FDC (Fault Detection and Classification) data and product quality, i.e., wafer metrology, which should be considered simultaneously for developing improved R2R controllers. In this paper, the equipment condition is explicitly modeled and integrated into the core of a R2R controller, in order to accommodate this critical aspect of the system in deriving the control law, in order to reduce process variability in more effective way. Therefore, a new R2R control framework is proposed, which is called: Controller with Real-time Equipment Condition (CREC). The effectiveness of the new control strategy is demonstrated and validated using the case study of a Chemical-Mechanical Polishing (CMP) process, in collaboration with our industrial partner.","PeriodicalId":349004,"journal":{"name":"2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128579569","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: 2

In-line XPS to quantify the changes in interfacial layers of advanced node gate stacks 在线XPS量化高级节点栅极堆叠界面层的变化

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373182

M. Medikonda, B. Kannan, B. Cohen, V. Chhabra, K. Onishi, G. Dilliway, A. Bello, M. Klare

引用次数: 1

Metal CMP process optimization for low abrasive slurry 低磨料浆金属CMP工艺优化

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373168

S. Mukherjee, Gagan Aggarwal

引用次数: 3

Patterning challenges for monolithic silicon photonics: AP/DFM: Advanced patterning / design for manufacturability 单片硅光子学的图片化挑战:AP/DFM:可制造性的高级图片化/设计

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373178

Colleen Meagher, Z. Sowinski, Chienfan Yu, Shuren Hu, K. Nummy, M. Ghosal, Ramya Viswanathan, A. Abdo, T. Wiltshire

引用次数: 3

Alignment solutions on FBEOL layers using ASML scanners: AEPM: Advanced equipment processes and materials 使用ASML扫描仪的FBEOL层对准解决方案:AEPM:先进的设备工艺和材料

2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Pub Date : 2018-04-01 DOI: 10.1109/ASMC.2018.8373194

Pavan Samudrala, Gregory Hart, Yen-Jen Chen, Lokesh Subramany, Haiyong Gao, N. Aung, W. Chung, B. Minghetti, R. Mali, Seva Khikhlovskyi, P. Heres

{"title":"Alignment solutions on FBEOL layers using ASML scanners: AEPM: Advanced equipment processes and materials","authors":"Pavan Samudrala, Gregory Hart, Yen-Jen Chen, Lokesh Subramany, Haiyong Gao, N. Aung, W. Chung, B. Minghetti, R. Mali, Seva Khikhlovskyi, P. Heres","doi":"10.1109/ASMC.2018.8373194","DOIUrl":"https://doi.org/10.1109/ASMC.2018.8373194","url":null,"abstract":"Wafers at FBEOL layers traditionally have higher stress and larger alignment signal variability. ASML's ATHENA sensor based scanners, commonly used to expose FBEOL layers, have large spot size (∼700um). Hence ATHENA captures the signal from larger area compared to the alignment marks which are typically ∼40um wide. This results in higher noise in the alignment signal and if the surrounding areas contain periodic product structures, they interfere with the alignment signal causing either alignment rejects or in some cases-misalignment. SMASH alignment sensors with smaller spot size (∼40um) and two additional probe lasers have been used to improve alignment quality and hence reduce mark/wafer rejects. However, due to the process variability, alignment issues still persist. For example, the aluminum grain size, alignment mark trench deposition uniformity, alignment mark asymmetry and variation in stack thicknesses all contribute to the alignment signal variability even within a single wafer. Here, a solution using SMASH sensor that involves designing new alignment marks to ensure conformal coating is proposed. Also new techniques and controls during coarse wafer alignment (COWA) and fine wafer alignment (FIWA) including extra controls over wafer shape parameters, longer scan lengths on alignment marks and weighted light source between Far Infra-Red laser (FIR) and Near Infra-Red (NIR) for alignment are presented. All the above mentioned techniques, when implemented, have reduced the wafer alignment reject rate from around 36% to less than 0.1%. Future work includes mark validation based on the signal response from the various laser colors. Finally, process monitoring using alignment parameters is explored.","PeriodicalId":349004,"journal":{"name":"2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127054891","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