机器学习方法在材料研究中的应用探索
首发时间:2021-01-20
摘要:由于材料内在关系的复杂性,传统的材料研究方法存在周期长、成本高以及具有一定的偶然性等不足,无法满足当下对材料研发的需求。随着大数据的巨大成功,机器学习越来越展现其独到的优势。本文综述了利用机器学习对钙钛矿材料、金属材料、非晶材料、复合材料进行相关性能预测,并指出了机器学习在材料合成与预测方向上的发展方向。
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Application and Exploration of marchine learning methods in materials reseach
Abstract:Due to the complexity of the internal relationship of materials, the traditional material research methods have disadvantages such as long cycle, high cost and contingency, which cannot meet the current requirements of material research and development. With the great success of big data, machine learning is showing its unique advantages more and more. This paper reviews the performance prediction of perovskite materials, metal materials, amorphous materials and composite materials using machine learning, and points out the development direction of machine learning in the direction of material synthesis and prediction.
Keywords: Machine learning performance prediction Material synthesis and prediction
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