journal article·2019-08-13

Large-Scale Computational Identification of p-Type Oxide Semiconductors by Hierarchical Screening

Yong Youn, Miso Lee, Doyeon Kim, Jae Kyeong Jeong, Youngho Kang, Seungwu Han

Chemistry of Materials· Volume 31· Issue 15
Publisher page

Abstract

With potentials to outperform traditional semiconductors, oxide semiconductors are penetrating into a wide range of energy, environmental, and electronic applications. However, an insufficient library of p-type oxides is a major obstacle against complete oxide electronics. To identify promising p-type oxides, we carry out a large-scale computational screening over 17,700 oxygen-containing compounds using the hydrogen descriptor that was shown to select the p-type oxide reliably. To enable high-throughput screening, we use in the initial stage coarse but simple descriptors that correlate with the hydrogen descriptor. Through a hierarchical screening procedure, we find 156 p-type oxides with the band gap larger than 1.1 eV, discovering promising candidates such as NaNbO2 and La2SiO4Se and also new types of p-type oxides. Furthermore, we classify the identified p-type oxides according to the valence-band character and reveal chemical principles underlying the p-type dopability.
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Research context

OpenAlex topics: Electronic and Structural Properties of Oxides · Machine Learning in Materials Science · Advanced Photocatalysis Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Materials Science and Engineering and Research Institute of Advanced Materials, Seoul National University, Seoul 08826, Korea

Department of Electronic Engineering, Hanyang University, Seoul 04763, Korea

Materials Data Center, Korea Institute of Materials Science, Changwon 51508, Korea

Funding

Samsung · Korea Institute of Materials Science

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