{"title":"Secondary electron spectroscopy for imaging semiconductor materials","authors":"T. Agemura, T. Sekiguchi","doi":"10.1109/ISSM.2018.8651171","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651171","url":null,"abstract":"The “fountain detector (FD)”, which is a low-pass secondary electron detector in a scanning electron microscope (SEM), has been developed in order to visualize the surface potential variation or the dopant density for semiconductor materials. A 4H-SiC p-n junction, which has different dopant densities in the p-region, was observed and energy spectra with FD were compared to the spectra with Auger spectra across the p-n junction. The energy spectra with FD shows the same tendency on those spectra with Auger and clearly identify differences between not only p- and n-regions but the different dopant densities in p-region.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"875 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123024183","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}
M. Pfeffer, C. Zängle, A. Bauer, G. Schneider, P. Franze
{"title":"Advanced Wafer Container Contamination Control Methods and Strategies in Power Device Manufacturing","authors":"M. Pfeffer, C. Zängle, A. Bauer, G. Schneider, P. Franze","doi":"10.1109/ISSM.2018.8651151","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651151","url":null,"abstract":"Power devices and power electronic systems are key components in various applications. Driven by market and volume requirements manufacturers are moving towards fully automated 300 mm manufacturing lines, which typically utilize closed wafer containers like FOUPs (Front Opening Unified Pods) and FOSBs (Front Opening Shipping Boxes). Power semiconductor manufacturing technologies require very complex tool dedications in order to increase yield and to avoid excursions in electrical performance due to critical contaminants like AMC (airborne molecular contamination). An optimized cleaning and contamination monitoring strategy for wafer containers will rely on advanced sampling and analysis capabilities, which need to be further elaborated.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114341966","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}
M. Fujikawa, J. de Marneffe, R. Chanson, K. Gavan, A. Rezvanov, F. Lazzarino, Z. Tokei, T. Yamaguchi, S. Nozawa, N. Sato
{"title":"Gas Phase Pore Stuffing for the protection of organo-silicate glass dielectric materials","authors":"M. Fujikawa, J. de Marneffe, R. Chanson, K. Gavan, A. Rezvanov, F. Lazzarino, Z. Tokei, T. Yamaguchi, S. Nozawa, N. Sato","doi":"10.1109/ISSM.2018.8651158","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651158","url":null,"abstract":"Plasma induced damage on porous low-k dielectrics is a critical issue for lowering the interconnect RC delay in densely packed CMOS transistors. In this paper, we propose a new approach to protect the pores on porous organo-silicate glasses (OSG) during plasma process, so-called Gas Phase Pore Stuffing (GPPS).","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129133945","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}
{"title":"Outlier Screening for Advanced Automotive Applications","authors":"Cinti Chen, Po-Hsien Chang, Xiao-Yu Li","doi":"10.1109/ISSM.2018.8651136","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651136","url":null,"abstract":"Rapid adoption of semiconductor devices in automotive industry, especially for self-driving cars, has demanded stringent reliability and quality requirements on them. How to apply various test strategies and innovative methods to detect and filter out outlier devices that could impose reliability issues has become a challenge that every fab and fabless company has to face with urgency and open mind. In this paper, the authors have reported various algorithms and techniques to dynamically identify outliers among devices for automotive applications. These methodologies have provided significant competitive advantages in manufacturing process monitoring, product quality improvement, and product qualifications.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134514992","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}
{"title":"Novel CMP technology for removal rate control of SiN","authors":"T. Shinoda, A. Endou, K. Sugai","doi":"10.1109/issm.2018.8651168","DOIUrl":"https://doi.org/10.1109/issm.2018.8651168","url":null,"abstract":"A novel model was proposed to control the removal rate (RR) for SiN with chemical additives having (1) the functions to approach to the SiN substrate and to adsorb on it and (2) the functions to react with the SiN substrate and to change the strength of Si – N bonds. By using the computational chemistry methods, these functions were justified, and the ratios of the model RR for SiN were also calculated. These ratios were in agreement with those of the experimental RR for SiN, which demonstrated the validity of our novel model.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126556048","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}
T. Tsutsumi, Y. Fuknaga, K. Ishikawa, H. Kondo, M. Sekine, M. Hori
{"title":"Real-time control of a wafer temperature for uniform plasma process","authors":"T. Tsutsumi, Y. Fuknaga, K. Ishikawa, H. Kondo, M. Sekine, M. Hori","doi":"10.1109/ISSM.2018.8651183","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651183","url":null,"abstract":"Our developed non-contact method for measurement of temperature of silicon (Si) wafer by using autocorrelation-type fourier domain low coherence interferometer has advantageous in accuracy and rapid response. We demonstrate measurements in temperature for Si wafer at real-time during plasma process and in estimation of heat flux to the wafer from plasma, involving heats balanced plasma source and conductive loss in Si. The analysis indicated that other heat sources like the chamber parts with relatively high temperature impact on the duty ratio during the process with feedback control of the wafer teperture.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126815893","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}
Shota Suzuki, Tomohiko Akatsuka, A. Endou, K. Sugai
{"title":"Study on Mechanisms of SiO2-CMP","authors":"Shota Suzuki, Tomohiko Akatsuka, A. Endou, K. Sugai","doi":"10.1109/issm.2018.8651181","DOIUrl":"https://doi.org/10.1109/issm.2018.8651181","url":null,"abstract":"Polishing slurries for SiO<inf>2</inf>-CMP have been found to specifically enhance the material removal rate for SiO<inf>2</inf> under certain condition. By extracting its key parameter, further enhancement of the removal rate for SiO<inf>2</inf> is expected. In this study, key parameters to enhance removal rate for SiO<inf>2</inf> were investigated based on the consideration of the polishing mechanisms of SiO<inf>2</inf>. It was found that the most effective parameter was the adhesion force of abrasive particles to SiO<inf>2</inf>.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131353612","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}
{"title":"Logistics Management Innovation, RFID Application on Intelligent Management of Valuable Assets","authors":"Y. Lin, K. Lin","doi":"10.1109/ISSM.2018.8651150","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651150","url":null,"abstract":"A company’s storage inventory accuracy and information instant realization are the key points to the logistics operation.UMC has acted as a leader in the field of semiconductor manufacturing since warehouse members took the first step of intelligent management by introducing RFID system to gas operation in 2015. In the view of our experience and achievement, as well as the evaluation of RFID applications, we have decided to apply RFID system for Dry Pump’s management.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122982688","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}
{"title":"Virtual Metrology Model Robustness Against Chamber Condition Variation by Using Deep Learning","authors":"T. Tsutsui, Takahito Matsuzawa","doi":"10.1109/issm.2018.8651170","DOIUrl":"https://doi.org/10.1109/issm.2018.8651170","url":null,"abstract":"In these days, deep learning (DL) [1] is attracting a lot of interest due to their highly discriminative representations that have outperformed many state-of-the-art techniques, mainly in the field of computer vision (CV). In this article, we exhibit a new DL method that exploits the semiconductor domain knowledge and extracts the informative features from optical emission spectroscopy (OES) data, that have both wavelengths and time spatial information. The virtual metrology (VM) is the target functionality, as it is difficult to get a robust model by conventional methods. As a comparison, two other well-known DL methods were also evaluated. The evaluation was executed on a real industrial dataset related to the etch process, which is one of the most important semiconductor manufacturing processes.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124974411","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}