Predicting the interfacial thermal resistance of electronic packaging materials via machine learning-Reference-Cited by-同舟云学术

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Predicting the interfacial thermal resistance of electronic packaging materials via machine learning

Published:2022-08-10 Issue: Volume: Page:
ISSN:
Container-title:2022 23rd International Conference on Electronic Packaging Technology (ICEPT)
language:
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Author:

Wang Nanyu¹,Jieensi Jiayidaer²,Zhen Zheng²,Zhou Yanguang³,Ju Shenghong¹

Affiliation:

1. Shanghai Jiao Tong University,China-UK Low Carbon College,Shanghai,China

2. Shanghai Jiao Tong University,School of Material Science and Engineering,Shanghai,China

3. The Hong Kong University of Science and Technology,Department of Mechanical and Aerospace Engineering,Hong Kong,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9872527/9872536/09872718.pdf?arnumber=9872718

Reference18 articles.

1. AFLOW: An automatic framework for high-throughput materials discovery

2. Leibniz Institute for Information Infrastructure;Karlsruhe FIZ Karlsruhe,2020

3. The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies

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