D. Kong, D. Schmidt, M. Breton, A. A. de la peña, J. Frougier, A. Greene, Jingyun Zhang, V. Basker, N. Loubet, I. Ahsan, A. Cepler, M. Klare, Marjorie Cheng, R. Koret, I. Turovets
{"title":"Development of SiGe Indentation Process Control to Enable Stacked Nanosheet FET Technology","authors":"D. Kong, D. Schmidt, M. Breton, A. A. de la peña, J. Frougier, A. Greene, Jingyun Zhang, V. Basker, N. Loubet, I. Ahsan, A. Cepler, M. Klare, Marjorie Cheng, R. Koret, I. Turovets","doi":"10.1109/ASMC49169.2020.9185226","DOIUrl":null,"url":null,"abstract":"The methodology of measuring the lateral etch, or indentation, of SiGe nanosheets by using optical scatterometry, x-ray fluorescence, and machine learning algorithms is presented and discussed. Stacked nanosheet device structures were fabricated with different etch conditions in order to induce variations in the indent. It was found that both scatterometry in conjunction with Spectral Interferometry and novel interpretation algorithms as well as TEM calibrated LE-XRF are suitable techniques to quantify the indent. Machine learning algorithms enabled an additional solution path by combining LE-XRF data with scatterometry spectra therefore avoiding the need for a full optical model.","PeriodicalId":6771,"journal":{"name":"2020 31st Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"137 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 31st Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASMC49169.2020.9185226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The methodology of measuring the lateral etch, or indentation, of SiGe nanosheets by using optical scatterometry, x-ray fluorescence, and machine learning algorithms is presented and discussed. Stacked nanosheet device structures were fabricated with different etch conditions in order to induce variations in the indent. It was found that both scatterometry in conjunction with Spectral Interferometry and novel interpretation algorithms as well as TEM calibrated LE-XRF are suitable techniques to quantify the indent. Machine learning algorithms enabled an additional solution path by combining LE-XRF data with scatterometry spectra therefore avoiding the need for a full optical model.
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