Effect of internal structure of a batch-processing wet-etch reactor on fluid flow and heat transfer

被引:0
|
作者
Deng, Qinghang [1 ]
Weng, Junqi [1 ]
Zhou, Lei [1 ]
Ye, Guanghua [1 ]
Zhou, Xinggui [1 ]
机构
[1] East China Univ Sci & Technol, Sch Chem Engn, State Key Lab Chem Engn, Shanghai 200237, Peoples R China
基金
中国国家自然科学基金; 上海市自然科学基金;
关键词
Wet-etch reactor; Batch-processing; Computational fluid dynamics; Reaction heat; Internal structure; Etch uniformity; SILICON-NITRIDE; PHOSPHORIC-ACID; SIMULATION; SI3N4/SIO2; KINETICS; DIOXIDE; SURFACE; DESIGN; FILMS;
D O I
10.1016/j.cjche.2024.05.002
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Batch-processing wet-etch reactors are the key equipment widely used in chip fabrication, and their performance is largely affected by the internal structure. This work develops a three-dimensional computational fluid dynamics (CFD) model considering heat generation of wet-etching reactions to investigate the fluid flow and heat transfer in the wet-etch reactor. The backflow is observed below and above the wafer region, as the flow resistance in this region is high. The temperature on the upper part of a wafer is higher due to the accumulation of reaction heat, and the average temperature of the side wafer is highest as its convective heat transfer is weakest. Narrowing the gap between wafer and reactor wall can force the etchant to flow in the wafer region and then facilitate the convective heat transfer, leading to better within-wafer and wafer-to-wafer etch uniformities. An inlet angle of 60 degrees balances fluid by-pass and mechanical energy loss, and it yields the best temperature and etch uniformities. The batch with 25 wafers has much wider flow channels and much lower flow resistance compared with that with 50 wafers, and thus it shows better temperature and etch uniformities. These results and the CFD model should serve to guide the optimal design of batch-processing wet-etch reactors. (c) 2024 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:177 / 186
页数:10
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