Mapping Oxidation and Wafer Cleaning to Device Characteristics Using Physics-Assisted Machine Learning-Reference-Cited by-同舟云学术

Mapping Oxidation and Wafer Cleaning to Device Characteristics Using Physics-Assisted Machine Learning

Published:2022-01-03 Issue:1 Volume:7 Page:933-946
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Pratik Sparsh¹^ORCID,Liu Po-Ning¹^ORCID,Ota Jun¹²^ORCID,Tu Yen-Liang¹^ORCID,Lai Guan-Wen¹^ORCID,Ho Ya-Wen¹^ORCID,Yang Zheng-Kai¹^ORCID,Rawat Tejender Singh¹^ORCID,Lin Albert S.¹^ORCID

Affiliation:

1. Institute of Electronics Engineering, National Yang Ming Chiao-Tung University, Hsinchu City 30010, Taiwan, R.O.C.

2. Imari Crystal Engineering Section, Crystal Engineering Department, Technology Division, SUMCO Corporation, Saga 849-0506, Japan

Funder

Ministry of Science and Technology, Taiwan

Taiwan Semiconductor Research Institute

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.1c05552

Reference64 articles.

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2. Artificial neural networks for fast and accurate EM-CAD of microwave circuits

3. Neural-Based Models of Semiconductor Devices for SPICE Simulator

4. Zhang, Z.; Wang, R.; Chen, C.; Huang, Q.; Wang, Y.; Hu, C.; Wu, D.; Wang, J.; Huang, R. New-Generation Design-Technology Co-Optimization (DTCO): Machine-Learning Assisted Modeling Framework. arXiv.org, 2019, 1904.10269.

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