A model-based, Bayesian approach to the CF4/Ar trench etch of SiO2
A model-based, Bayesian approach to the CF4/Ar trench etch of SiO2
复制标题
基于模型的贝叶斯方法对 SiO2 进行 CF4/Ar 沟槽蚀刻
DOI：
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
R. Bonnecaze
中科院分区：
文献类型：
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作者：
Meghali Chopra;Sofia Helpert;R. Verma;Zizhuo Zhang;Xilan Zhu;R. Bonnecaze
像等离子体刻蚀这样的高度非线性和复杂工艺的设计和优化是具有挑战性和耗时的。为了方便刻蚀配方的开发，已经投入了大量的努力来创造等离子体轮廓模拟器。然而，由于等离子体放电和刻蚀材料表面动力学中的大量未知参数、刻蚀速率对不断演变的前沿轮廓的依赖以及系统的不同长度尺度，这些模拟器往往难以在实践中使用。在这里，我们详述了在平台Rodeo(沉积和蚀刻的配方优化)中体现的先前发表的数据通知的贝叶斯方法的发展。Rodeo用于预测CF4/Ar气体化学的各种功率、压力、气体流量和气体混合比范围内的蚀刻速率和蚀刻剖面。给出了三个例子：(1)用CF4/Ar化学模拟实验预测未知材料“X”的刻蚀速率；(2)用CF4/Ar化学模拟实验预测等离子体温度790RIE反应器中SiO_2的刻蚀速率；(3)用Level Set方法预测轮廓。
The design and optimization of highly nonlinear and complex processes like plasma etching is challenging and timeconsuming. Significant effort has been devoted to creating plasma profile simulators to facilitate the development of etch recipes. Nevertheless, these simulators are often difficult to use in practice due to the large number of unknown parameters in the plasma discharge and surface kinetics of the etch material, the dependency of the etch rate on the evolving front profile, and the disparate length scales of the system. Here, we expand on the development of a previously published, data informed, Bayesian approach embodied in the platform RODEo (Recipe Optimization for Deposition and Etching). RODEo is used to predict etch rates and etch profiles over a range of powers, pressures, gas flow rates, and gas mixing ratios of an CF4/Ar gas chemistry. Three examples are shown: (1) etch rate predictions of an unknown material “X” using simulated experiments for a CF4/Ar chemistry, (2) etch rate predictions of SiO2 in a Plasma-Therm 790 RIE reactor for a CF4/Ar chemistry, and (3) profile prediction using level set methods.
用于生化调控系统建模中测量集选择的 Maximin 和贝叶斯稳健实验设计
影响因子：
3.9
作者：
He, Fei;Brown, Martin;Yue, Hong
通讯作者：
Yue, Hong