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機械学習の役割 材料の理解と設計
Seyed Mohamad Moosavi1, Kevin Maik Jablonka1, Berend Smit1
1Laboratory of Molecular Simulation, Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Rue de l'Industrie 17, CH-1951 Sion, Valais, Switzerland.
Journal of the American Chemical Society
|November 10, 2020
まとめ
機械学習は 複雑な検索空間をナビゲートすることで 合理的な素材の設計を加速します このアプローチは,重要な技術的,社会的利点を持つ新しい材料を発見するための体系的な経路を提供します.
科学分野:
- 材料科学
- コンピュータ化学
- 人工知能
背景:
- 新しい材料の合理的な設計は 技術の進歩にとって不可欠です
- 従来の方法では 物質の発見の複雑さに 苦労しています
- 機械学習 (ML) はこれらの課題を克服するための強力なツールを提供します.
研究 の 目的:
- 合理的な材料設計のためのMLの進歩をレビューする.
- この分野における現在の課題と将来の機会を議論する.
- 材料の発見の将来について 視点を提供するためです
主な方法:
- 材料科学に適用された機械学習アルゴリズムのレビュー.
- 特性予測とプロセスの設計におけるMLアプリケーションの分析.
- テクノ・エコノミック・アセスメントの統合
主要な成果:
- MLは物質の探査を大幅に強化します
- アルゴリズムによるアプローチは 新材料の発見を効率化します
- MLは,材料設計プロセスの全体的な見方を容易にする.
結論:
- 機械学習は 合理的な材料設計のための 変革のツールです
- 現在の課題に取り組むことで 材料発見のさらなる可能性が 解き放たれます
- 材料科学の未来は 人工知能が主導するアプローチによって 形作られていくでしょう
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