Accelerating discovery of next-generation power electronics materials via high-throughput ab initio screening

IF 11.9 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Jiashu Chen, Mingzhu Liu, Minghui Liu, Xinzhong Wang, Yiwen Su, Guangping Zheng
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Abstract

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.

Abstract Image

通过高通量从头算筛选加速下一代电力电子材料的发现
电力电子(pe)在从消费设备到工业基础设施的应用中发挥着关键作用。宽带隙(WBG)半导体如SiC、GaN和Ga2O3已成为pe中的高性能材料。然而,WBG材料存在固有缺陷扩散、制造成本过高等局限性。基于高通量计算方法,我们确定了SiC, GaN和Ga2O3以外的下一代pe材料。利用从头算方法对带隙、电子迁移率、热导率以及Baliga和Johnson优值(bbfom和JFOM)进行全面评估,筛选了一个包含153235种材料的庞大数据库。全面而有效的理论分析确定了一些有前途的候选材料(B2O3、BeO和BN),它们具有高的bbfom、JFOM和晶格导热系数。我们的方法可以扩展到电子的其他应用领域,简化探索新材料的过程。
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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
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.
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