No Cover Image

Journal article 194 views 144 downloads

A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3

Zhanpeng Sun Orcid Logo, Zijun Qi Orcid Logo, Kang Liang Orcid Logo, Xiang Sun Orcid Logo, Zhaofu Zhang Orcid Logo, Lijie Li Orcid Logo, Qijun Wang Orcid Logo, Guoqing Zhang Orcid Logo, Gai Wu Orcid Logo, Wei Shen Orcid Logo

Applied Physics Letters, Volume: 123, Issue: 19

Swansea University Author: Lijie Li Orcid Logo

  • APL23-AR-WBEX2023-05013.pdf

    PDF | Accepted Manuscript

    Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy.

    Download (1.07MB)

Check full text

DOI (Published version): 10.1063/5.0165320

Abstract

Ga2O3 is an ultrawide-bandgap semiconductor with a variety of crystal configurations, which has the potential for a variety of applications, especially in power electronics and ultraviolet optoelectronics. However, there has been no single interatomic potential reported for Ga2O3 polymorphs in terms...

Full description

Published in: Applied Physics Letters
ISSN: 0003-6951 1077-3118
Published: AIP Publishing 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa64954
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2023-11-09T16:50:49Z
last_indexed 2023-11-09T16:50:49Z
id cronfa64954
recordtype SURis
fullrecord <?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>64954</id><entry>2023-11-09</entry><title>A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3</title><swanseaauthors><author><sid>ed2c658b77679a28e4c1dcf95af06bd6</sid><ORCID>0000-0003-4630-7692</ORCID><firstname>Lijie</firstname><surname>Li</surname><name>Lijie Li</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2023-11-09</date><deptcode>EEEG</deptcode><abstract>Ga2O3 is an ultrawide-bandgap semiconductor with a variety of crystal configurations, which has the potential for a variety of applications, especially in power electronics and ultraviolet optoelectronics. However, there has been no single interatomic potential reported for Ga2O3 polymorphs in terms of molecular dynamics prediction of thermal conductivity. Here, one interatomic potential has been developed based on neural networks, which has the clear advantages of consuming less computational power than density functional theory and has high accuracy in predicting the thermal conductivity of the three polymorphs of Ga2O3. Using the neuroevolution potential, the thermal conductivity values at 300 K have been predicted. Hence, the κ[average-α] was 67.2% that of β-Ga2O3, and the κ[average-ε] was only 26.4% that of β-Ga2O3. The possible reasons for the discrepancies in thermal conductivity values in various crystal types and orientations have been explored. As a result, it could be shown that the contribution of low-frequency phonons to thermal conductivity was very significant in Ga2O3, and a unit cell with low symmetry and high atomic number would negatively impact the thermal conductivity of the material. In this work, a scheme has been proposed for accurately predicting the thermal conductivity of Ga2O3 and a relatively accurate value of the thermal conductivity of ε-Ga2O3 has been achieved, which could also provide an atomic-scale perspective for the insight into the thermal conductivity differences among α, β, and ε-Ga2O3.</abstract><type>Journal Article</type><journal>Applied Physics Letters</journal><volume>123</volume><journalNumber>19</journalNumber><paginationStart/><paginationEnd/><publisher>AIP Publishing</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0003-6951</issnPrint><issnElectronic>1077-3118</issnElectronic><keywords>Thermal conductivity, crystal configurations, power electronics, neuroevolution potential</keywords><publishedDay>6</publishedDay><publishedMonth>11</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-11-06</publishedDate><doi>10.1063/5.0165320</doi><url>http://dx.doi.org/10.1063/5.0165320</url><notes/><college>COLLEGE NANME</college><department>Electronic and Electrical Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>EEEG</DepartmentCode><institution>Swansea University</institution><apcterm>Not Required</apcterm><funders>This work was funded by the National Natural Science Foundation of China (Grant Nos. 62004141 and 52202045), the Fundamental Research Funds for the Central Universities (Grant Nos. 2042022kf1028 and 2042023kf0112), the Major Program of Hubei Province (Grant No. 2023BAA009), the Knowledge Innovation Program of Wuhan-Shuguang (Grant Nos. 2023010201020243 and 2023010201020255), the Hubei Natural Science Foundation (Grant No. 2022CFB606), and the Open Fund of Hubei Key Laboratory of Electronic Manufacturing and Packaging Integration (Grant No. EMPI2023027).</funders><projectreference/><lastEdited>2023-12-05T14:06:24.8085553</lastEdited><Created>2023-11-09T16:45:33.3928511</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering</level></path><authors><author><firstname>Zhanpeng</firstname><surname>Sun</surname><orcid>0009-0009-7268-7984</orcid><order>1</order></author><author><firstname>Zijun</firstname><surname>Qi</surname><orcid>0000-0002-4440-5734</orcid><order>2</order></author><author><firstname>Kang</firstname><surname>Liang</surname><orcid>0000-0003-4812-3539</orcid><order>3</order></author><author><firstname>Xiang</firstname><surname>Sun</surname><orcid>0000-0002-7619-9648</orcid><order>4</order></author><author><firstname>Zhaofu</firstname><surname>Zhang</surname><orcid>0000-0002-1406-1256</orcid><order>5</order></author><author><firstname>Lijie</firstname><surname>Li</surname><orcid>0000-0003-4630-7692</orcid><order>6</order></author><author><firstname>Qijun</firstname><surname>Wang</surname><orcid>0000-0002-4299-3798</orcid><order>7</order></author><author><firstname>Guoqing</firstname><surname>Zhang</surname><orcid>0000-0003-4618-9892</orcid><order>8</order></author><author><firstname>Gai</firstname><surname>Wu</surname><orcid>0000-0002-9726-6328</orcid><order>9</order></author><author><firstname>Wei</firstname><surname>Shen</surname><orcid>0000-0003-4389-3112</orcid><order>10</order></author></authors><documents><document><filename>64954__28984__a43b80f69f6b4bde9303444d59ec2191.pdf</filename><originalFilename>APL23-AR-WBEX2023-05013.pdf</originalFilename><uploaded>2023-11-09T16:50:25.3352142</uploaded><type>Output</type><contentLength>1119923</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><documentNotes>Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling v2 64954 2023-11-09 A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3 ed2c658b77679a28e4c1dcf95af06bd6 0000-0003-4630-7692 Lijie Li Lijie Li true false 2023-11-09 EEEG Ga2O3 is an ultrawide-bandgap semiconductor with a variety of crystal configurations, which has the potential for a variety of applications, especially in power electronics and ultraviolet optoelectronics. However, there has been no single interatomic potential reported for Ga2O3 polymorphs in terms of molecular dynamics prediction of thermal conductivity. Here, one interatomic potential has been developed based on neural networks, which has the clear advantages of consuming less computational power than density functional theory and has high accuracy in predicting the thermal conductivity of the three polymorphs of Ga2O3. Using the neuroevolution potential, the thermal conductivity values at 300 K have been predicted. Hence, the κ[average-α] was 67.2% that of β-Ga2O3, and the κ[average-ε] was only 26.4% that of β-Ga2O3. The possible reasons for the discrepancies in thermal conductivity values in various crystal types and orientations have been explored. As a result, it could be shown that the contribution of low-frequency phonons to thermal conductivity was very significant in Ga2O3, and a unit cell with low symmetry and high atomic number would negatively impact the thermal conductivity of the material. In this work, a scheme has been proposed for accurately predicting the thermal conductivity of Ga2O3 and a relatively accurate value of the thermal conductivity of ε-Ga2O3 has been achieved, which could also provide an atomic-scale perspective for the insight into the thermal conductivity differences among α, β, and ε-Ga2O3. Journal Article Applied Physics Letters 123 19 AIP Publishing 0003-6951 1077-3118 Thermal conductivity, crystal configurations, power electronics, neuroevolution potential 6 11 2023 2023-11-06 10.1063/5.0165320 http://dx.doi.org/10.1063/5.0165320 COLLEGE NANME Electronic and Electrical Engineering COLLEGE CODE EEEG Swansea University Not Required This work was funded by the National Natural Science Foundation of China (Grant Nos. 62004141 and 52202045), the Fundamental Research Funds for the Central Universities (Grant Nos. 2042022kf1028 and 2042023kf0112), the Major Program of Hubei Province (Grant No. 2023BAA009), the Knowledge Innovation Program of Wuhan-Shuguang (Grant Nos. 2023010201020243 and 2023010201020255), the Hubei Natural Science Foundation (Grant No. 2022CFB606), and the Open Fund of Hubei Key Laboratory of Electronic Manufacturing and Packaging Integration (Grant No. EMPI2023027). 2023-12-05T14:06:24.8085553 2023-11-09T16:45:33.3928511 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Zhanpeng Sun 0009-0009-7268-7984 1 Zijun Qi 0000-0002-4440-5734 2 Kang Liang 0000-0003-4812-3539 3 Xiang Sun 0000-0002-7619-9648 4 Zhaofu Zhang 0000-0002-1406-1256 5 Lijie Li 0000-0003-4630-7692 6 Qijun Wang 0000-0002-4299-3798 7 Guoqing Zhang 0000-0003-4618-9892 8 Gai Wu 0000-0002-9726-6328 9 Wei Shen 0000-0003-4389-3112 10 64954__28984__a43b80f69f6b4bde9303444d59ec2191.pdf APL23-AR-WBEX2023-05013.pdf 2023-11-09T16:50:25.3352142 Output 1119923 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy. true eng https://creativecommons.org/licenses/by/4.0/
title A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3
spellingShingle A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3
Lijie Li
title_short A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3
title_full A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3
title_fullStr A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3
title_full_unstemmed A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3
title_sort A neuroevolution potential for predicting the thermal conductivity of α, β, and ε-Ga2O3
author_id_str_mv ed2c658b77679a28e4c1dcf95af06bd6
author_id_fullname_str_mv ed2c658b77679a28e4c1dcf95af06bd6_***_Lijie Li
author Lijie Li
author2 Zhanpeng Sun
Zijun Qi
Kang Liang
Xiang Sun
Zhaofu Zhang
Lijie Li
Qijun Wang
Guoqing Zhang
Gai Wu
Wei Shen
format Journal article
container_title Applied Physics Letters
container_volume 123
container_issue 19
publishDate 2023
institution Swansea University
issn 0003-6951
1077-3118
doi_str_mv 10.1063/5.0165320
publisher AIP Publishing
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
url http://dx.doi.org/10.1063/5.0165320
document_store_str 1
active_str 0
description Ga2O3 is an ultrawide-bandgap semiconductor with a variety of crystal configurations, which has the potential for a variety of applications, especially in power electronics and ultraviolet optoelectronics. However, there has been no single interatomic potential reported for Ga2O3 polymorphs in terms of molecular dynamics prediction of thermal conductivity. Here, one interatomic potential has been developed based on neural networks, which has the clear advantages of consuming less computational power than density functional theory and has high accuracy in predicting the thermal conductivity of the three polymorphs of Ga2O3. Using the neuroevolution potential, the thermal conductivity values at 300 K have been predicted. Hence, the κ[average-α] was 67.2% that of β-Ga2O3, and the κ[average-ε] was only 26.4% that of β-Ga2O3. The possible reasons for the discrepancies in thermal conductivity values in various crystal types and orientations have been explored. As a result, it could be shown that the contribution of low-frequency phonons to thermal conductivity was very significant in Ga2O3, and a unit cell with low symmetry and high atomic number would negatively impact the thermal conductivity of the material. In this work, a scheme has been proposed for accurately predicting the thermal conductivity of Ga2O3 and a relatively accurate value of the thermal conductivity of ε-Ga2O3 has been achieved, which could also provide an atomic-scale perspective for the insight into the thermal conductivity differences among α, β, and ε-Ga2O3.
published_date 2023-11-06T14:06:25Z
_version_ 1784451102698110976
score 11.013148

Similar Items