| Project/Area Number |
17H01318
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Inorganic materials/Physical properties
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
Oba Fumiyasu 東京工業大学, 科学技術創成研究院, 教授 (90378795)
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| Co-Investigator(Kenkyū-buntansha) |
赤松 寛文 九州大学, 工学研究院, 准教授 (10776537)
田中 功 京都大学, 工学研究科, 教授 (70183861)
平松 秀典 東京工業大学, 科学技術創成研究院, 准教授 (80598136)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥43,290,000 (Direct Cost: ¥33,300,000、Indirect Cost: ¥9,990,000)
Fiscal Year 2019: ¥11,570,000 (Direct Cost: ¥8,900,000、Indirect Cost: ¥2,670,000)
Fiscal Year 2018: ¥11,310,000 (Direct Cost: ¥8,700,000、Indirect Cost: ¥2,610,000)
Fiscal Year 2017: ¥9,100,000 (Direct Cost: ¥7,000,000、Indirect Cost: ¥2,100,000)
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| Keywords | 窒化物半導体 / 材料設計 / 第一原理計算 / 点欠陥 / 薄膜 / 格子欠陥 / ドーピング |
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| Outline of Final Research Achievements |
Promising new nitride semiconductors were proposed by in silico materials design and screening of candidate materials based on accurate and multifaceted first-principles calculations and machine learning. Design and selection guidelines were constructed based on detailed theoretical investigations of known nitride semiconductors, and several promising materials were identified by in silico screening using these guidelines. Moreover, theoretical predictions on bandgap tuning and carrier doping of selected nitride semiconductors were experimentally verified.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では理論計算、機械学習と合成・評価実験の密接な連携により、窒化物半導体の設計・探索・創製を行った。これは、近年注目を集めている計算科学並びにマテリアルズインフォマティクス手法による効率的な材料設計・探索の好例と言え、有効な材料研究手法の提案という観点からも意義深いと言える。また、本研究では窒化物半導体の設計・探索を主題としたが、本アプローチは他の材料系への応用も見込めることから、波及効果が大きいと考えられる。
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