机器学习在材料理解和设计中的作用
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
概括
机器学习可以通过复杂的搜索空间来加速合理的材料设计. 这种方法为发现具有重大技术和社会效益的新材料提供了系统的途径.
科学领域:
- 材料科学
- 计算化学
- 人工智能
背景情况:
- 新材料的合理设计对于技术进步至关重要.
- 传统的方法难以应对材料的巨大复杂性.
- 机器学习 (ML) 为克服这些挑战提供了强大的工具.
研究的目的:
- 审查合理材料设计的ML方面的进展.
- 讨论当前的挑战和未来的机会.
- 提供对未来材料发现的视角.
主要方法:
- 对材料科学应用的机器学习算法的审查.
- 在性能预测和工艺设计中分析ML应用.
- 探索技术经济评估的整合.
主要成果:
- ML显著增强了材料空间的探索.
- 算法方法简化了新材料的发现.
- ML 能够提供对材料设计过程的整体视图.
结论:
- 机器学习是合理材料设计的变革性工具.
- 应对当前的挑战将释放材料发现的进一步潜力.
- 材料科学的未来将越来越多地由人工智能驱动的方法塑造.
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