Asli Sirman, Fuad H. Al-amoody, Chandar Palamadai, B. Saville, Ankit Jain, Kha X. Tran
{"title":"利用雾霾监测的a-Si针孔检测和表征:CFM:无污染制造","authors":"Asli Sirman, Fuad H. Al-amoody, Chandar Palamadai, B. Saville, Ankit Jain, Kha X. Tran","doi":"10.1109/ASMC.2019.8791809","DOIUrl":null,"url":null,"abstract":"This paper describes a novel methodology for identifying pinholes (defects in thin films) in an amorphous silicon (a-Si) film using a KLA Surfscan® SP5 laser scattering-based unpatterned wafer inspection system. Inherent to the deposition mechanism, pinholes exist at the interface between a-Si/substrate. It is crucial to find the optimized film thickness that is free of pinholes. In this study we developed a unique process monitoring method adapted to quantify pinhole defects using surface haze. Haze is the background scattering signal of the wafer obtained from the inspection system [1] and the defect signal from scanning electron microscope (SEM) images from an eDR® e-beam defect review system. A macro program was developed to automatically process the SEM images and quantify the defect signal. A strong correlation between haze and a-Si pinhole count was observed. The method can be extended to different films including SiN, TiN and similar scenarios, where unconventional defect detection methods are needed.","PeriodicalId":287541,"journal":{"name":"2019 30th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"285 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"a-Si Pinhole Detection and Characterization using Haze Monitoring : CFM: Contamination Free Manufacturing\",\"authors\":\"Asli Sirman, Fuad H. Al-amoody, Chandar Palamadai, B. Saville, Ankit Jain, Kha X. Tran\",\"doi\":\"10.1109/ASMC.2019.8791809\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a novel methodology for identifying pinholes (defects in thin films) in an amorphous silicon (a-Si) film using a KLA Surfscan® SP5 laser scattering-based unpatterned wafer inspection system. Inherent to the deposition mechanism, pinholes exist at the interface between a-Si/substrate. It is crucial to find the optimized film thickness that is free of pinholes. In this study we developed a unique process monitoring method adapted to quantify pinhole defects using surface haze. Haze is the background scattering signal of the wafer obtained from the inspection system [1] and the defect signal from scanning electron microscope (SEM) images from an eDR® e-beam defect review system. A macro program was developed to automatically process the SEM images and quantify the defect signal. A strong correlation between haze and a-Si pinhole count was observed. The method can be extended to different films including SiN, TiN and similar scenarios, where unconventional defect detection methods are needed.\",\"PeriodicalId\":287541,\"journal\":{\"name\":\"2019 30th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)\",\"volume\":\"285 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 30th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASMC.2019.8791809\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 30th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASMC.2019.8791809","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
a-Si Pinhole Detection and Characterization using Haze Monitoring : CFM: Contamination Free Manufacturing
This paper describes a novel methodology for identifying pinholes (defects in thin films) in an amorphous silicon (a-Si) film using a KLA Surfscan® SP5 laser scattering-based unpatterned wafer inspection system. Inherent to the deposition mechanism, pinholes exist at the interface between a-Si/substrate. It is crucial to find the optimized film thickness that is free of pinholes. In this study we developed a unique process monitoring method adapted to quantify pinhole defects using surface haze. Haze is the background scattering signal of the wafer obtained from the inspection system [1] and the defect signal from scanning electron microscope (SEM) images from an eDR® e-beam defect review system. A macro program was developed to automatically process the SEM images and quantify the defect signal. A strong correlation between haze and a-Si pinhole count was observed. The method can be extended to different films including SiN, TiN and similar scenarios, where unconventional defect detection methods are needed.