Scientific Machine Learning Enables Multiphysics Digital Twins of Large-Scale Electronic Chips-Reference-Cited by-同舟云学术

Scientific Machine Learning Enables Multiphysics Digital Twins of Large-Scale Electronic Chips

Published:2022-12 Issue:12 Volume:70 Page:5305-5318
ISSN:0018-9480
Container-title:IEEE Transactions on Microwave Theory and Techniques
language:
Short-container-title:IEEE Trans. Microwave Theory Techn.

Author:

Li Xiao¹,Zhan Qiwei¹^ORCID,Sun Bozhao¹,Feng Haoqiang¹,Zeng Yonghu²,Wang Huabing²,Yang Xiaofan²^ORCID,Yin Wen-Yan¹^ORCID

Affiliation:

1. Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang Province, Innovative Institute of Electromagnetic Information and Electronic Integration, College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

2. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang Electronic Equipment Test Center, Luoyang, China

Funder

NSFC

CEMEE

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

http://xplorestaging.ieee.org/ielx7/22/9979645/09924250.pdf?arnumber=9924250

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1. Effects of TSVs (through-silicon vias) on thermal performances of 3D IC integration system-in-package (SiP)

2. POD-based model order reduction with an adaptive snapshot selection for a discontinuous Galerkin approximation of the time-domain Maxwell's equations