Gwanjoong Kim;Ji-Won Kwon;Ingyu Lee;Hwiwon Seo;Jong-Bae Park;Jong-Hyeon Shin;Gon-Ho Kim
{"title":"Application of Plasma Information-Based Virtual Metrology (PI-VM) for Etching in C₄F₈/Ar/O₂ Plasma","authors":"Gwanjoong Kim;Ji-Won Kwon;Ingyu Lee;Hwiwon Seo;Jong-Bae Park;Jong-Hyeon Shin;Gon-Ho Kim","doi":"10.1109/TSM.2024.3447074","DOIUrl":null,"url":null,"abstract":"This study developed Plasma Information-based Virtual Metrology (PI-VM) to predict etching process results and analyze process phenomena. Using a dual-frequency capacitively coupled plasma (CCP) etcher with C4F8/Ar/O2 plasma, we etched low aspect ratio (AR) trench patterns in amorphous carbon layer (ACL) hard masks and \n<inline-formula> <tex-math>$\\rm SiO_{2}$ </tex-math></inline-formula>\n molds, and developed the PI-VM statistically by integrating plasma information (PI) variables that reflect domain knowledge. The passivation effect of fluorocarbon plasma was analyzed by varying the gas ratios and the effect of ion energy was analyzed by changing the low frequency (LF) power. In the PI-VM results, the density ratios of the passivation precursor \n<inline-formula> <tex-math>$\\rm CF_{2}$ </tex-math></inline-formula>\n to the etchant F and O were selected as key factors for predicting the process. The selection of radical density ratios as features confirmed the dominance of plasma chemistry in low AR etching. Demonstrating high predictive accuracy with minimal data, PI-VM offers significant potential to enhance the development of semiconductor process recipes.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"37 4","pages":"602-614"},"PeriodicalIF":2.3000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Semiconductor Manufacturing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10643189/","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This study developed Plasma Information-based Virtual Metrology (PI-VM) to predict etching process results and analyze process phenomena. Using a dual-frequency capacitively coupled plasma (CCP) etcher with C4F8/Ar/O2 plasma, we etched low aspect ratio (AR) trench patterns in amorphous carbon layer (ACL) hard masks and
$\rm SiO_{2}$
molds, and developed the PI-VM statistically by integrating plasma information (PI) variables that reflect domain knowledge. The passivation effect of fluorocarbon plasma was analyzed by varying the gas ratios and the effect of ion energy was analyzed by changing the low frequency (LF) power. In the PI-VM results, the density ratios of the passivation precursor
$\rm CF_{2}$
to the etchant F and O were selected as key factors for predicting the process. The selection of radical density ratios as features confirmed the dominance of plasma chemistry in low AR etching. Demonstrating high predictive accuracy with minimal data, PI-VM offers significant potential to enhance the development of semiconductor process recipes.
期刊介绍:
The IEEE Transactions on Semiconductor Manufacturing addresses the challenging problems of manufacturing complex microelectronic components, especially very large scale integrated circuits (VLSI). Manufacturing these products requires precision micropatterning, precise control of materials properties, ultraclean work environments, and complex interactions of chemical, physical, electrical and mechanical processes.