Fumiyasu Oba
;
Takayuki Nagai
;
Ryoji Katsube
;
Yasuhide Mochizuki
;
Masatake Tsuji
;
Guillaume Deffrennes
;
Kota Hanzawa
;
Akitoshi Nakano
;
Akira Takahashi
;
Kei Terayama
;
Ryo Tamura
(National Institute for Materials Science
)
;
Hidenori Hiramatsu
;
Yoshitaro Nose
;
Hiroki Taniguchi
Collection
Citation
Description:
(abstract)Computational approaches using theoretical calculations and data scientific methods have become increasingly important in materials science and technology, with the development of relevant methodologies and algorithms, the availability of large materials data, and the enhancement of computer performance. As reviewed herein, we have developed computational methods for the design and prediction of inorganic materials with a particular focus on the exploration of semiconductors and dielectrics. High-throughput first-principles calculations are used to systematically and accurately predict the local atomic and electronic structures of polarons, point defects, surfaces, and interfaces, as well as bulk fundamental properties. Machine learning techniques are utilized to efficiently predict various material properties, construct phase diagrams, and search for materials satisfying target properties. These computational approaches have elucidated the mechanisms behind material functionalities and explored promising materials in combination with synthesis, characterization, and device fabrication. Examples include the development of ternary nitride semiconductors for potential optoelectronic and photovoltaic applications, the exploration of phosphide semiconductors and the optimization of heterointerfaces toward the improvement of phosphide-based photovoltaic cells, and the discovery of ferroelectricity in layered perovskite oxides and the theoretical understanding of its origin, all of which demonstrate the effectiveness of our computer-aided materials research.
Rights:
Keyword: semiconductors, dielectrics
Date published: 2024-12-31
Publisher: Informa UK Limited
Journal:
- Science and Technology of Advanced Materials (ISSN: 14686996) vol. 25 issue. 1
Funding:
- the CREST
- Japan Science and Technology Corporation
Manuscript type: Publisher's version (Version of record)
MDR DOI:
First published URL: https://doi.org/10.1080/14686996.2024.2423600
Related item:
Other identifier(s):
Contact agent:
Updated at: 2024-12-25 16:31:05 +0900
Published on MDR: 2024-12-26 08:30:42 +0900
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