数据与计算发展前沿 ›› 2020, Vol. 2 ›› Issue (2): 78-90.doi: 10.11871/jfdc.issn.2096-742X.2020.02.006

• 专刊: 数据分析技术与应用 • 上一篇    下一篇

材料科学数据库在材料研发中的应用与展望

李姿昕1,2,3,张能1,2,3,熊斌1,2,3,胡云凤1,2,3,赵新鹏1,2,3,黄海友1,2,3,*()   

  1. 1. 新材料技术研究院,北京科技大学,北京 100083
    2. 北京材料基因工程高精尖创新中心,北京科技大学,北京 100083
    3. 材料基因工程北京市重点实验室,北京科技大学,北京 100083
  • 收稿日期:2020-02-16 出版日期:2020-04-20 发布日期:2020-06-03
  • 通讯作者: 黄海友 E-mail:huanghy@mater.ustb.edu.cn
  • 作者简介:李姿昕,北京科技大学新材料技术研究院,在读研究生,主要研究方向为机器学习。
    本文承担工作为:数据库平台概述,以及论文的写作与修改。
    Li Zixin is a master student at Institute for Advanced Materials and Technology, University of Science and Technology Beijing. Her main research interest is machine learning.
    In this paper she undertakes the following tasks: organizing the review on the development of database, as well as the writing and revision of manuscript.
    E-mail: s20191363@xs.ustb.edu.cn|张能,北京科技大学新材料技术研究院,在读研究生,主要研究方向为基于机器学习方法的Cu-Al合金断裂性能研究。
    本文承担工作为:数据库应用的分析与讨论,以及论文的写作与修改。
    Zhang Neng is a master student at Institute for Advanced Materials and Technology, University of Science and Technology Beijing. His main research interest is machine learning based research on fracture properties of Cu-Al alloys.
    In this paper he undertakes the following takes: analysis and discussion of database applications, as well as the writing and revision of manuscript.
    E-mail: s20191421@xs.ustb.edu.cn|熊斌,北京科技大学新材料技术研究院,在读研究生,主要研究方向为机器学习方法在形状记忆合金马氏体相变研究中的应用。
    本文承担工作为:文献的整理、查阅。
    Xiong Bin is a master student at Institute for Advanced Materials and Technology, University of Science and Technology Beijing. His main research interest is machine learning based research on martensite transformation of shape memory alloys.
    In this paper he undertakes the following tasks: collecting and summarizing references.
    E-mail: g20189313@xs.ustb.edu.cn|胡云凤,北京科技大学新材料技术研究院,在读研究生,主要研究方向为高弹热效应形状记忆合金以及机器学习。
    本文承担工作为:文献的整理、查阅。
    Hu Yunfeng is a master student at Institute for Advanced Materials and Technology, University of Science and Technology Beijing. Her main research interests are focusing on high elastocaloric effect shape memory alloys and machine learning.
    In this paper she undertakes the following tasks: collecting and summarizing references.
    E-mail: s20181326@xs.ustb.edu.cn|赵新鹏,北京科技大学新材料技术研究院,硕士,主要研究方向为第一性原理计算,机器学习以及高弹热效应形状记忆合金。
    本文承担工作为:数据库在机器学习中的应用分析与讨论以及全文统筹。
    Zhao Xinpeng, master, is studying at Institute for Advanced Materials and Technology, University of Science and Technology Beijing. His main research interests are First-principles calculations, machine learning and high elastocaloric effect shape memory alloys.
    In this paper he undertakes the following tasks: conceptualizing and organizing the review on the application of database in machine learning.
    E-mail: g20179183@ustb.cn|黄海友,北京科技大学新材料技术研究院,工学博士,副研究员。在Applied Physics Letters,APL Materials,Scripta Materials等期刊上发表学术论文61 篇。授权发明专利5项;参编著作3部;2017年获教育部自然科学奖二等奖。主要研究方向包括材料基因工程数据库与大数据技术,基于数据驱动的新材料研发和形状记忆合金等。
    本文承担工作为:总体架构和主要思路。
    Huang Haiyou, D.E, is an associate research fellow at Institute for Advanced Materials and Technology, University of Science and Technology Beijing. He has published more than 60 academic papers in Applied Physics Letters, APL Materials, Scripta Materials and other journals. He also has authorized 5 invention patents, edited 3 books and won the second prize of the Natural Science Award of the Ministry of Education in 2017. His main research interests are materials genome engineering database, big data technology, data-driven development method of new materials and shape memory alloys, etc.
    In this paper he undertakes the following tasks: constructing manuscript structure and making up main ideas.
  • 基金资助:
    国家重点研发计划资助项目(2016YFB0700500,2018YFB0704300);广东省重点领域研发计划项目(2019B010940001);北京科技大学顺德研究生院科技创新专项资金(BK19BE030)

Materials Science Database in Material Research and Development: Recent Applications and Prospects

Li Zixin1,2,3,Zhang Neng1,2,3,Xiong Bin1,2,3,Hu Yunfeng1,2,3,Zhao Xinpeng1,2,3,Huang Haiyou1,2,3,*()   

  1. 1. Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, China
    2. Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China
    3. Beijing Key Laboratory of Materials Genome Initiative, University of Science and Technology Beijing, Beijing 100083, China
  • Received:2020-02-16 Online:2020-04-20 Published:2020-06-03
  • Contact: Haiyou Huang E-mail:huanghy@mater.ustb.edu.cn

摘要:

[目的]随着“大数据”时代的来临,大数据技术由于可显著加速材料研发,已经成为材料科学研究者关注的热点技术之一。基于材料数据库平台的材料大数据技术更是成为“材料基因工程”的三大核心技术之一。因此,材料数据库建设对于加速新材料的研发至关重要。[方法]本文通过对国内外材料科学数据库的建设及应用的概括和总结,并结合材料科学数据库的发展趋势,提出了未来的研究方向。[结果]材料基因组(工程)理念的提出和大数据技术的快速发展,促进了国内外大量材料科学数据库的建立。相较国外而言,国内的材料科学数据库建设相对较晚。但在“十三五”国家重点研发计划专项的支持下,我国材料科学数据库平台建设有望在未来几年内取得初步成效。[结论]材料科学数据库的建设已经成为材料基因工程技术发展进程当中一种不可或缺的要素,但在数据库建设和应用过程中还存在很多困难亟待解决,材料科学数据库的发展仍任重道远。

关键词: 数据库, 大数据技术, 材料信息学, 材料基因工程, 机器学习

Abstract:

[Objective] With the advent of the "Big Data" era, big data technology has become one of the hottest technologies attracting material science researchers because it can significantly accelerate the development of materials. The material big data technology based on the material database platform is one of the three core technologies of "Materials Genome Engineering". Therefore, the construction of a material database is very important to acceleration of the development of new materials. [Methods] This article summarizes the constructions and applications of material science databases at home and abroad, and puts forward future research directions based on the development trend of material science databases. [Results] The advancement of the material genome (engineering) concept and the rapid development of big data technologies have promoted the establishment of a large number of material science databases at home and abroad. Compared with developed countries, the material science database construction in China is relatively late. However, with the support of the ‘Thirteenth Five-Year Plan’ national key research and development program of China, the construction of China's material science database platform is expected to achieve initial results in the next few years. [Conclusions] The construction of material science database has become an indispensable element in the development process of material genome engineering technology. But there are still many difficulties to be resolved in the process of database construction and application. The development of a material science database remains a challenging task.

Key words: database, big data technology, material informatics, material genome engineering, machine learning