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複雑な無機相場における2種類の結晶構造の加速発見
C Collins1, M S Dyer1, M J Pitcher1
1Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, UK.
Nature
|June 9, 2017
まとめ
研究者は計算による予測と実験的合成を組み合わせて 新しい無機物質を発見した. このアプローチは複雑な構成空間を効率的に探索し,新しい結晶構造とユニークな性質を持つ材料の発見を加速します.
科学分野:
- 材料科学
- コンピュータ化学
- 固体化学
背景:
- 新しい材料,特に複雑な無機固体の発見は,膨大な数の可能な組成と構造のために困難です.
- 伝統的な方法は結晶化学の知識と時間を要する合成に依存し,新しい構造の探索を制限しています.
- 計算的方法は構造や組成を予測するのに役立ちますが,複雑なシステムで完全に新しい,実験的に実行可能な結晶構造を見つけるのに苦労します.
研究 の 目的:
- 新しい無機物質と結晶構造を発見するための効率的な計算実験的アプローチを開発し,実証する.
- 複雑な組成空間を探索し,新しい,安定した化合物を特定する制限を克服する.
- 段階図の有望で未知の領域に実験合成を導くことにより,材料の発見を加速する.
主な方法:
- 新しい構造型を含む複雑な無機相場内の計算的に特定された領域.
- エネルギーランキングのための化学的,構造的な多様性を捉えるために,多様な"探査構造"を生成した.
- 低エネルギー候補を特定するために,既知の材料に対して計算された構造をランク付けします.
- 最低エネルギー領域から 実験的に合成した物質です
主要な成果:
- 2つの新しい無機物質構造を発見した.
- これまでに報告されていない結晶構造と異常な構造モチーフを持つ物質を特定した.
- 複雑なシステムにおける実験合成を効率的に導くための計算アプローチを検証した.
結論:
- 複雑な構成空間における新しい材料の識別を大幅に加速します.
- この方法は,実験的に検証された新しい構造で知識基盤を拡張することによって,計算ツールの予測力を高めます.
- この戦略は,実験的に実現可能な新しい化合物を体系的に発見し,材料科学を前進させることを約束しています.
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