摘要
化学气相沉积技术是一种近几十年发展起来的制备无机材料的化工技术。随着机器学习技术的发展,其在化学气相沉积领域也发挥着不小的作用。基于此,本文概述了化学气相沉积的原理与机器学习的发展历程,分析了机器学习在化学气相沉积中的典型应用,总结并分析了未来应用的发展趋势。
Chemical vapor deposition technology is a chemical technology for preparing inorganic materials developed in recent decades.With the development of machine learning technology,it also plays a significant role in the field of chemical vapor deposition.Based on this,this paper firstly outlines the principles of chemical vapor deposition and the development of machine learning,then analyzes the typical applications of machine learning in chemical vapor deposition,and finally summarizes and analyzes the development trend of future applications.
作者
谢炜
明帅强
夏洋
周兰江
XIE Wei;MING Shuaiqiang;XIA Yang;ZHOU Lanjiang(School of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650000,China;Jiaxing Zhongke Microelectronics Instrument and Equipment Engineering Center,Jiaxing 314000,China)
出处
《材料科学与工程学报》
CAS
CSCD
北大核心
2024年第2期331-339,共9页
Journal of Materials Science and Engineering
基金
中科院关键技术团队资助项目(GJJSTD20200003)。
关键词
化学气相沉积
无机材料
薄膜
机器学习
Chemical vapor deposition
Inorganic material
Film
Machine learning
