摘要
材料不仅是国民经济的基础,而且也是高新技术的载体.超越常规手段、应用新方法加速新材料的研发已成为全世界的研究热点.随着数据驱动方法取得的巨大成功,机器学习受到了日益高度的关注.它结合计算机科学、数据库理论、统计学、计算数学和工程学,不仅能展现出更快的计算速度和可靠的预测能力,大幅度提升材料计算效率,而且还能有效地处理一些难以运用传统模拟计算方法解决的体系和问题,这为研发具有特殊功能和特殊结构的新材料以满足日益提升的新技术的要求提供了契机.本文将简要概述机器学习的基本原理,介绍机器学习模型中的几种典型算法以及机器学习在新材料研究中的应用进展,并对机器学习在材料科学领域中的未来的发展前景做出展望.
Materials are not only the foundation of the national economy, but also the carrier of high technology. It has become a research hotspot in the world to overcome the conventional methods and apply new methods to accelerate the development of new materials. Propelled by the great success in other fields, data-driven informatics methods begin to emerge as a new technique in material science. Machine learning, as a representative of data-driven methods, has received extensive attention in various fields. Machine learning is an interdisciplinary science that combines computer science, statistics, computational mathematics and engineering. In the field of materials science, machine learning methods show faster calculation speed and higher prediction accuracy compared with conventional theoretical computational simulations based on solving physical or chemical fundamental equations. Machine learning is an effective addition to the existing theoretical calculation methods and significantly increases the efficiency of materials computational simulation work. Furthermore, it also works for some systems or problems that the traditional theoretical calculation methods fail to solve. This approach could also enable targeted material design and development. This review would provide a brief overview on the fundamentals of machine learning, several typical algorithms in machine learning and the applications in materials science, and discuss the future challenges in this field.
作者
吴炜
孙强
WU Wei1,2, SUN Qiang1,2.(Department of Materials Science and Engineering, College of Engineering, Peking University, Beijing 100871, China; 2Center for Applied Physics and Technology, Peking University, Beijing 100871, China)
出处
《中国科学：物理学、力学、天文学》
CSCD
北大核心
2018年第10期54-66,共13页
Scientia Sinica Physica,Mechanica & Astronomica
基金
国家自然科学基金(编号:21573008
21773003)
国家重点研发项目(编号:2016YFB0100200
2017YFA0204902)资助
关键词
新材料
机器学习
材料计算模拟
new materials
machine learning
computation and simulation
