Search for superconducting hydrogen compounds by integration approach of computational and data sciences
| Project/Area Number |
17K05541
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Condensed matter physics II
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| Research Institution | National Institute for Materials Science (2018-2019)
Osaka University (2017) |
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Principal Investigator |
ISHIKAWA Takahiro 国立研究開発法人物質・材料研究機構, 磁性・スピントロニクス材料研究拠点, NIMS特別研究員 (40423082)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2019: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
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| Keywords | 超伝導 / 高圧 / 水素化合物 / 進化的アルゴリズム / 第一原理計算 / 遺伝的アルゴリズム / 遺伝的プログラミング / 機械学習 / 結晶構造 / 第一原理電子状態計算 / データ科学 / 進化論的手法 / 高温超伝導 |
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| Outline of Final Research Achievements |
Compressed hydrogen compounds are attracting attention as candidates for room-temperature superconductivity. The number of combinations, however, is significantly large, and data scientific approaches are useful for the search. In the present study, I developed an original methodology for materials search, which is the integration approach of computational high-pressure science and data science, and applied it to the search for novel superconducting hydrogen compounds. I collected the data on hydrogen compounds from literature, developed the superconductivity predictor from the data using an evolutionary technique, and predicted potential candidates. I obtained the results that ternary hydrogen compounds consisting of the group 1-3 and 13-16 elements have a potential to show high-temperature superconductivity. I verified their superconductivities using first-principles calculations, and obtained 122 kelvin in KScH12 and 98 kelvin in GaAsH6.
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| Academic Significance and Societal Importance of the Research Achievements |
結晶構造探索プログラムの独自開発・改良を行いながら高圧物質科学に応用しているグループは世界的に見ても数が少なく、進化的手法を基礎とする計算高圧科学とデータ科学の融合はまだ誰も試みていない独自の研究方法となるため、本研究を達成できれば他のグループでは実施できない独創的で挑戦的な研究を行うことが可能となる。高圧極限環境下では物質の物理的・化学的性質が常圧のものから大きく変化し、物質の隠された姿が明らかになる。本研究によって得られる物質の結晶構造、電子状態、超伝導性などに関するデータや知見は、超伝導物質だけでなく、その他の機能性物質の探索・設計にも応用できる。
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Report
(4 results)
Research Products
(35 results)
