Apeksha Gupta, Karthik Shathiri, Vidyasagar Shilapuram, M. Ramachandran
{"title":"用响应面法研究锗化学机械抛光工艺参数及抛光浆成分","authors":"Apeksha Gupta, Karthik Shathiri, Vidyasagar Shilapuram, M. Ramachandran","doi":"10.1504/ijmpt.2021.115823","DOIUrl":null,"url":null,"abstract":"Chemical mechanical polishing/planarisation (CMP) stays a widely used process for complete planarisation in semiconductor fabrication. CMP process provides surface uniformity, high selectivity, low defects with the desired material removal rate. The removal rate is influenced by various independent parameters namely turntable speed, down pressure, slurry pH, and H2O2 concentration. Modelling the CMP process from fundamental principles is limited. Hence, in this study, the design of the experimental methodology has been adopted to design the CMP process. Different models such as linear, quadratic, two-factor interaction, and cubic mathematical were developed and statistically analysed in identifying the suitable model by Box-Behnken design. The consequence of each parameter and their interactions on Ge removal rate is analysed. A quadratic model is proposed from the outcome. The predicted values achieved using model equations exhibited appropriate fit by experimental values (R2 value for rutile and anatase as 0.943 and 0.942, respectively). The present work verified that response surface methodology and Box-Behnken design can be expeditiously functional for modelling of chemical mechanical planarisation.","PeriodicalId":14167,"journal":{"name":"International Journal of Materials & Product Technology","volume":" ","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigation of polishing parameters and slurry composition on germanium chemical mechanical planarisation using response surface methodology\",\"authors\":\"Apeksha Gupta, Karthik Shathiri, Vidyasagar Shilapuram, M. Ramachandran\",\"doi\":\"10.1504/ijmpt.2021.115823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Chemical mechanical polishing/planarisation (CMP) stays a widely used process for complete planarisation in semiconductor fabrication. CMP process provides surface uniformity, high selectivity, low defects with the desired material removal rate. The removal rate is influenced by various independent parameters namely turntable speed, down pressure, slurry pH, and H2O2 concentration. Modelling the CMP process from fundamental principles is limited. Hence, in this study, the design of the experimental methodology has been adopted to design the CMP process. Different models such as linear, quadratic, two-factor interaction, and cubic mathematical were developed and statistically analysed in identifying the suitable model by Box-Behnken design. The consequence of each parameter and their interactions on Ge removal rate is analysed. A quadratic model is proposed from the outcome. The predicted values achieved using model equations exhibited appropriate fit by experimental values (R2 value for rutile and anatase as 0.943 and 0.942, respectively). The present work verified that response surface methodology and Box-Behnken design can be expeditiously functional for modelling of chemical mechanical planarisation.\",\"PeriodicalId\":14167,\"journal\":{\"name\":\"International Journal of Materials & Product Technology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2021-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Materials & Product Technology\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1504/ijmpt.2021.115823\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Materials & Product Technology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1504/ijmpt.2021.115823","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Investigation of polishing parameters and slurry composition on germanium chemical mechanical planarisation using response surface methodology
Chemical mechanical polishing/planarisation (CMP) stays a widely used process for complete planarisation in semiconductor fabrication. CMP process provides surface uniformity, high selectivity, low defects with the desired material removal rate. The removal rate is influenced by various independent parameters namely turntable speed, down pressure, slurry pH, and H2O2 concentration. Modelling the CMP process from fundamental principles is limited. Hence, in this study, the design of the experimental methodology has been adopted to design the CMP process. Different models such as linear, quadratic, two-factor interaction, and cubic mathematical were developed and statistically analysed in identifying the suitable model by Box-Behnken design. The consequence of each parameter and their interactions on Ge removal rate is analysed. A quadratic model is proposed from the outcome. The predicted values achieved using model equations exhibited appropriate fit by experimental values (R2 value for rutile and anatase as 0.943 and 0.942, respectively). The present work verified that response surface methodology and Box-Behnken design can be expeditiously functional for modelling of chemical mechanical planarisation.
期刊介绍:
The IJMPT is a refereed and authoritative publication which provides a forum for the exchange of information and ideas between materials academics and engineers working in university research departments and research institutes, and manufacturing, marketing and process managers, designers, technologists and research and development engineers working in industry.