Asli Sirman, Fuad H. Al-amoody, Chandar Palamadai, B. Saville, Ankit Jain, Kha X. Tran
{"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}
引用次数: 1
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.