数据与计算发展前沿 ›› 2021, Vol. 3 ›› Issue (2): 120-132.doi: 10.11871/jfdc.issn.2096-742X.2021.02.014

• 技术与应用 • 上一篇    下一篇

基于计算机技术的材料研发方法概述

郭佳龙1,2(),王宗国1,2,*(),王彦棡1,2(),赵旭山1(),宿彦京3(),刘志威1,2()   

  1. 1.中国科学院计算机网络信息中心,北京 100190
    2.中国科学院大学,北京 100049
    3.北京科技大学新材料技术研究院,北京 100083
  • 收稿日期:2020-12-11 出版日期:2021-04-20 发布日期:2021-05-18
  • 通讯作者: 王宗国
  • 作者简介:郭佳龙,中国科学院计算机网络信息中心,硕士研究生,主要研究方向为材料信息学。本文承担工作为文献的搜集整理以及整体内容的撰写。
    GUO Jialong is a master student of Com-puter Network Information Center, Chin-ese Academy of Sciences. His major research field is material informatics.
    In this paper, he is responsible for collective literature reviews and thesis writing.
    E-mail: guojialong@cnic.cn|王宗国,中国科学院计算机网络信息中心,副研究员,主要研究方向为材料信息学。
    本文承担的工作为架构构建和论文的指导。
    WANG Zongguo is an associate professor of Computer Network Information Center, Chinese Academy of Sciences. Her major research field is material informatics.
    In this paper, she is responsible for the construction of the architecture and the guidance of the paper.
    E-mail: wangzg@cnic.cn|王彦棡,中国科学院计算机网络信息中心,研究员,主要研究方向为人工智能算法与应用软件。
    本文承担的工作为思路凝练和论文的指导。
    WANG Yangang is a professor of Com-puter Network Information Center, Chinese Academy of Sciences. His major research field is artificial intelligence algorithm and application software.
    In this paper, he is responsible for the abstraction of ideas and the guidance of the paper.
    E-mail: wangyg@sccas.cn|赵旭山,中国科学院计算机网络信息中心,高级工程师,主要研究方向为材料信息学。
    本文承担的工作为文章框架设计。
    ZHAO Xushan is a senior engineer of Computer Network Information Center, Chinese Academy of Sciences. His major research field is material informatics.
    In this paper, he is responsible for designing the article frame-work.
    E-mail: xushan.zhao@hotmail.com|宿彦京,北京科技大学,教授,主要研究方向为材料数据科学与应用、材料氢脆与应力腐蚀微观机理。
    本文承担的工作为论文整体指导。
    SU Yanjing is a professor of University of Science and Technology Beijing. His major research directions are material data science and appli-cation, hydrogen embrittlement and micro mechanism of stress corrosion.
    In this paper, he is responsible for the guidance of the paper.
    E-mail: yjsu@ustb.edu.cn|刘志威,中国科学院计算机网络信息中心,硕士研究生,主要研究方向为材料信息学。
    本文承担工作为文献的搜集。
    LIU Zhiwei is a master student of Com-puter Network Information Center, Chinese Academy of Sciences. His major research field is material informatics.
    In this paper, he is responsible for literature collection.
    E-mail: liuzhiwei@cnic.cn
  • 基金资助:
    国家自然科学基金青年基金(51802312);国家自然科学基金青年基金(51701208);中国科学院信息化专项(XXH13506-410);中国科学院前沿科学重点研究计划(ZDBS-LY-7025)

A Review of Material Research and Development Methods Based on Computer Technology

GUO Jialong1,2(),WANG Zongguo1,2,*(),WANG Yangang1,2(),ZHAO Xushan1(),SU Yanjing3(),LIU Zhiwei1,2()   

  1. 1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, China
  • Received:2020-12-11 Online:2021-04-20 Published:2021-05-18
  • Contact: WANG Zongguo

摘要:

【目的】随着大数据时代的到来和材料基因组计划的提出,材料的研发模式开始由“试错法”向科学研究第四范式转变。本文主要针对新材料研发模式中涉及的计算机技术进行概述。【方法】作者跟踪调研了近年来材料计算科学和数据驱动材料研发的文献资料,对计算机技术在材料研发中的应用进行了总结和讨论。【结果】以材料计算科学和“数据+人工智能”驱动为基础的创新模式,可以显著提升材料研究效率,从多维度、新角度探索材料多参数或性能之间的关联关系。【结论】计算机技术在材料研发中的广泛应用对加快新材料研发、加深对材料的认知以及关键技术的突破具有重要意义。

关键词: 材料信息学, 机器学习, 数据驱动

Abstract:

[Objective] With the advent of the era of big data and the proposal of the Materials Genome Initiative, the research and development mode of materials has experienced a fundamental transformation from "trial and error" to the fourth paradigm of material science. This paper aims to summarize the computer technologies involved in this new materials research mode. [Methods] Based on the literatures on material computation and data-driven techniques in recent years, the paper summarizes and discusses the application of computer technologies in material research and development. [Results] The innovation mode marked by “data + artificial intelligence” and computational material science can improve the efficiency of material research significantly, and can explore the relationship between various material parameters and performance from multi-dimensional perspectives. [Conclusions] The application of computer technologies is of great importance to material research in accelerating progress, improving material understandings, and key technology breakthroughs.

Key words: material informatics, machine learning, data driven