Advances in machine learning have impacted myriad areas of materials science, ranging from the discovery of novel materials to the improvement of molecular simulations, with likely many more important developments to come. Given the rapid changes in this field, it is challenging to understand both the breadth of opportunities as well as best practices for their use. In this review, we address aspects of both problems by providing an overview of the areas where machine learning has recently had significant impact in materials science, and then provide a more detailed discussion on determining the accuracy and domain of applicability of some common types of machine learning models. Finally, we discuss some opportunities and challenges for the materials community to fully utilize the capabilities of machine learning.

中文翻译：

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材料科学中机器学习的机遇与挑战

机器学习的进步影响了材料科学的无数领域，从新材料的发现到分子模拟的改进，可能还有更多重要的发展。鉴于该领域的快速变化，了解机会的广度及其使用的最佳实践具有挑战性。在这篇综述中，我们通过概述机器学习最近对材料科学产生重大影响的领域来解决这两个问题的各个方面，然后更详细地讨论确定某些常见类型机器的准确性和适用范围学习模型。最后，我们讨论了材料社区充分利用机器学习能力的一些机遇和挑战。