工作流程
计算机科学
背景(考古学)
半导体
计算模型
材料科学
科学发现
纳米技术
数据科学
工程物理
吞吐量
光电子学
物理
人工智能
电信
无线
数据库
生物
古生物学
认知科学
心理学
作者
Shulin Luo,Tianshu Li,Xinjiang Wang,Muhammad Faizan,Lijun Zhang
摘要
Abstract In the recent past, optoelectronic semiconductors have attracted significant research attention both experimentally and theoretically toward large‐scale applications in energy conversion, lighting, imaging, detection, and so on. With advancement in computing power and rapid development of computational algorithms, scientific community resorts to materials simulation to explore the hidden potential behind thousands of potentially unknown materials within short timeframes that the real experiments might take a long time. Within this context, the high‐throughput (HT) computational materials screening has emerged as a useful tool to accelerate materials discovery, especially in the field of optoelectronic semiconductors. One of the important consequences is the construction of a number of material databases containing wide range of functional materials with their diverse physical properties and applications. Herein, we reviewed the recent progress on HT computational screening of optoelectronic semiconductors, with focus on photovoltaic solar absorbers, photoelectrochemical cells, semiconductor light‐emitting diodes, and transparent conducting materials. We have also summarized the general workflow of HT computational screening, released workhorse models, and existing material databases. Finally, we offer perspectives for future research with a hope that this study could inspire new ideas for computational‐driven optoelectronic semiconductor discovery in the HT routine. This article is categorized under: Structure and Mechanism > Computational Materials Science
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