Zhice Yang , Chaoran Ma , Yuxin Zhang , Zhuoyang Du , Peng Zhou , Yang Zhao , Tao Zhang , Fuhui Wang
{"title":"316L 不锈钢在半导体制造业使用的含微量水分的电子特殊气体下的腐蚀寿命预测模型","authors":"Zhice Yang , Chaoran Ma , Yuxin Zhang , Zhuoyang Du , Peng Zhou , Yang Zhao , Tao Zhang , Fuhui Wang","doi":"10.1016/j.corsci.2024.112510","DOIUrl":null,"url":null,"abstract":"<div><div>Special gases with trace moisture cause the formation of dynamic acidic microdroplets (DMD), which results in corrosion of semiconductor manufacturing devices. In this study, a predictive model for corrosion damage in 316L stainless steel (SS) was developed by combining the DMD process and the pitting initiation model. The DMD process was modeled using the BET model to describe the moisture-to-solution conversion. The pitting initiation model was reconstructed by incorporating the Sridhar model, temporal corrosion model, and Macdonald model. Finally, the predicted results were validated by various experimental data, indicating that the prediction model was accurate and highly reliable.</div></div>","PeriodicalId":290,"journal":{"name":"Corrosion Science","volume":"241 ","pages":"Article 112510"},"PeriodicalIF":7.4000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Corrosion-life prediction model for 316L stainless steel under electronic special gases containing trace moisture employed in semiconductor manufacturing industry\",\"authors\":\"Zhice Yang , Chaoran Ma , Yuxin Zhang , Zhuoyang Du , Peng Zhou , Yang Zhao , Tao Zhang , Fuhui Wang\",\"doi\":\"10.1016/j.corsci.2024.112510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Special gases with trace moisture cause the formation of dynamic acidic microdroplets (DMD), which results in corrosion of semiconductor manufacturing devices. In this study, a predictive model for corrosion damage in 316L stainless steel (SS) was developed by combining the DMD process and the pitting initiation model. The DMD process was modeled using the BET model to describe the moisture-to-solution conversion. The pitting initiation model was reconstructed by incorporating the Sridhar model, temporal corrosion model, and Macdonald model. Finally, the predicted results were validated by various experimental data, indicating that the prediction model was accurate and highly reliable.</div></div>\",\"PeriodicalId\":290,\"journal\":{\"name\":\"Corrosion Science\",\"volume\":\"241 \",\"pages\":\"Article 112510\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Corrosion Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0010938X24007054\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Corrosion Science","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010938X24007054","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Corrosion-life prediction model for 316L stainless steel under electronic special gases containing trace moisture employed in semiconductor manufacturing industry
Special gases with trace moisture cause the formation of dynamic acidic microdroplets (DMD), which results in corrosion of semiconductor manufacturing devices. In this study, a predictive model for corrosion damage in 316L stainless steel (SS) was developed by combining the DMD process and the pitting initiation model. The DMD process was modeled using the BET model to describe the moisture-to-solution conversion. The pitting initiation model was reconstructed by incorporating the Sridhar model, temporal corrosion model, and Macdonald model. Finally, the predicted results were validated by various experimental data, indicating that the prediction model was accurate and highly reliable.
期刊介绍：
Corrosion occurrence and its practical control encompass a vast array of scientific knowledge. Corrosion Science endeavors to serve as the conduit for the exchange of ideas, developments, and research across all facets of this field, encompassing both metallic and non-metallic corrosion. The scope of this international journal is broad and inclusive. Published papers span from highly theoretical inquiries to essentially practical applications, covering diverse areas such as high-temperature oxidation, passivity, anodic oxidation, biochemical corrosion, stress corrosion cracking, and corrosion control mechanisms and methodologies.
This journal publishes original papers and critical reviews across the spectrum of pure and applied corrosion, material degradation, and surface science and engineering. It serves as a crucial link connecting metallurgists, materials scientists, and researchers investigating corrosion and degradation phenomena. Join us in advancing knowledge and understanding in the vital field of corrosion science.
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