Efficient recommendation tool of materials by an executable file based on machine learning
Efficient recommendation tool of materials by an executable file based on machine learning
复制标题
DOI：
10.7567/1347-4065/ab349b
复制
发表时间：
2019-09-01
影响因子：
1.5
通讯作者：
Tamura, Ryo
中科院分区：
文献类型：
--
作者：
Terayama, Kei;Tsuda, Koji;Tamura, Ryo
为了加速新材料的发现，易于使用的材料信息学工具至关重要。我们开发材料信息学应用程序，可以在 Windows 计算机上执行，无需任何特殊设置。我们的应用程序有效地执行贝叶斯优化以优化材料属性和不确定性采样以完成新的相图。我们介绍了这些应用程序的用法，并显示了三元相图的采样结果。 (C) 2019 日本应用物理学会
To accelerate the discoveries of novel materials, an easy-to-use materials informatics tool is essential. We develop materials informatics applications, which can be executed on a Windows computer without any special settings. Our applications efficiently perform Bayesian optimization to optimize materials properties and uncertainty sampling to complete a new phase diagram. We introduce the usage of these applications and show the sampling results for a ternary phase diagram. (C) 2019 The Japan Society of Applied Physics