Machine learning and artificial neural network prediction of interfacial thermal resistance between graphene and hexagonal boron nitride-Reference-Cited by-同舟云学术

Machine learning and artificial neural network prediction of interfacial thermal resistance between graphene and hexagonal boron nitride

Published:2018 Issue:40 Volume:10 Page:19092-19099
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Yang Hong¹²³⁴^ORCID,Zhang Zhongtao⁵²³⁴,Zhang Jingchao⁵²³⁴^ORCID,Zeng Xiao Cheng¹²³⁴^ORCID

Affiliation:

1. Department of Chemistry

2. University of Nebraska-Lincoln

3. Lincoln

4. USA

5. Holland Computing Center

Abstract

Several machine learning algorithms and artificial neural network structures are used to predict the interfacial thermal resistance between single layer graphene and hexagonal boron nitride with only the knowledge of the system temperature, inter-layer coupling strength, and in-plane tensile strain.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2018/NR/C8NR05703F

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