{"title":"通过高通量从头算筛选加速下一代电力电子材料的发现","authors":"Jiashu Chen, Mingzhu Liu, Minghui Liu, Xinzhong Wang, Yiwen Su, Guangping Zheng","doi":"10.1038/s41524-025-01745-9","DOIUrl":null,"url":null,"abstract":"<p>Power electronics (PEs) play a pivotal role in electrical energy conversion and regulation for applications spanning from consumer devices to industrial infrastructure. Wide-bandgap (WBG) semiconductors such as SiC, GaN, and Ga<sub>2</sub>O<sub>3</sub> have emerged as high-performance materials in PEs. Nevertheless, the WBG materials have some limitations that there exists the proliferation of intrinsic defects, with prohibitively high fabrication costs. We identify next-generation PEs materials beyond SiC, GaN, and Ga<sub>2</sub>O<sub>3</sub> based on a high-throughput computational methodology. A massive database affording 153,235 materials is screened by leveraging ab initio methods with the thorough evaluation of bandgap, electron mobility, thermal conductivity, and Baliga and Johnson figures of merit (BFOM and JFOM). The comprehensive and effective theoretical analysis identifies some promising candidates (B<sub>2</sub>O<sub>3</sub>, BeO, and BN) that possess high BFOM, JFOM, and lattice thermal conductivity. Our methodology could be extended to other application domains of electronics, simplifying the process of exploring new materials.</p>","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"14 1","pages":""},"PeriodicalIF":11.9000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accelerating discovery of next-generation power electronics materials via high-throughput ab initio screening\",\"authors\":\"Jiashu Chen, Mingzhu Liu, Minghui Liu, Xinzhong Wang, Yiwen Su, Guangping Zheng\",\"doi\":\"10.1038/s41524-025-01745-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Power electronics (PEs) play a pivotal role in electrical energy conversion and regulation for applications spanning from consumer devices to industrial infrastructure. Wide-bandgap (WBG) semiconductors such as SiC, GaN, and Ga<sub>2</sub>O<sub>3</sub> have emerged as high-performance materials in PEs. Nevertheless, the WBG materials have some limitations that there exists the proliferation of intrinsic defects, with prohibitively high fabrication costs. We identify next-generation PEs materials beyond SiC, GaN, and Ga<sub>2</sub>O<sub>3</sub> based on a high-throughput computational methodology. A massive database affording 153,235 materials is screened by leveraging ab initio methods with the thorough evaluation of bandgap, electron mobility, thermal conductivity, and Baliga and Johnson figures of merit (BFOM and JFOM). The comprehensive and effective theoretical analysis identifies some promising candidates (B<sub>2</sub>O<sub>3</sub>, BeO, and BN) that possess high BFOM, JFOM, and lattice thermal conductivity. Our methodology could be extended to other application domains of electronics, simplifying the process of exploring new materials.</p>\",\"PeriodicalId\":19342,\"journal\":{\"name\":\"npj Computational Materials\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":11.9000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj Computational Materials\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1038/s41524-025-01745-9\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Computational Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1038/s41524-025-01745-9","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Accelerating discovery of next-generation power electronics materials via high-throughput ab initio screening
Power electronics (PEs) play a pivotal role in electrical energy conversion and regulation for applications spanning from consumer devices to industrial infrastructure. Wide-bandgap (WBG) semiconductors such as SiC, GaN, and Ga2O3 have emerged as high-performance materials in PEs. Nevertheless, the WBG materials have some limitations that there exists the proliferation of intrinsic defects, with prohibitively high fabrication costs. We identify next-generation PEs materials beyond SiC, GaN, and Ga2O3 based on a high-throughput computational methodology. A massive database affording 153,235 materials is screened by leveraging ab initio methods with the thorough evaluation of bandgap, electron mobility, thermal conductivity, and Baliga and Johnson figures of merit (BFOM and JFOM). The comprehensive and effective theoretical analysis identifies some promising candidates (B2O3, BeO, and BN) that possess high BFOM, JFOM, and lattice thermal conductivity. Our methodology could be extended to other application domains of electronics, simplifying the process of exploring new materials.
期刊介绍:
npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings.
Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.