Role of materials data science and informatics in accelerated materials innovation

被引:49
作者
Kalidindi, Surya R. [1 ]
Brough, David B. [2 ]
Li, Shengyen [3 ]
Cecen, Ahmet [2 ]
Blekh, Aleksandr L. [1 ]
Congo, Faical Yannick P. [4 ]
Campbell, Carelyn [4 ]
机构
[1] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Sch Computat Sci & Engn, Atlanta, GA 30332 USA
[3] NIST, Boulder, CO USA
[4] NIST, Mat Measurement Lab, Mat Sci & Engn Div, Boulder, CO USA
关键词
microstructure; metal; alloy; informatics; data; MATERIALS GENOME; CALIBRATION; ONTOLOGIES; FRAMEWORK;
D O I
10.1557/mrs.2016.164
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The goal of the Materials Genome Initiative is to substantially reduce the time and cost of materials design and deployment. Achieving this goal requires taking advantage of the recent advances in data and information sciences. This critical need has impelled the emergence of a new discipline, called materials data science and informatics. This emerging new discipline not only has to address the core scientific/technological challenges related to datafication of materials science and engineering, but also, a number of equally important challenges around data-driven transformation of the current culture, practices, and workflows employed for materials innovation. A comprehensive effort that addresses both of these aspects in a synergistic manner is likely to succeed in realizing the vision of scaled-up materials innovation. Key toolsets needed for the successful adoption of materials data science and informatics in materials innovation are identified and discussed in this article. Prototypical examples of emerging novel toolsets and their functionality are described along with select case studies.
引用
收藏
页码:596 / 602
页数:7
相关论文
共 60 条
  • [11] [Anonymous], 2014, MAT GEN IN STRAT PLA
  • [12] Considerations for choosing and using force fields and interatomic potentials in materials science and engineering
    Becker, Chandler A.
    Tavazza, Francesca
    Trautt, Zachary T.
    de Macedo, Robert A. Buarque
    [J]. CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE, 2013, 17 (06) : 277 - 283
  • [13] Bhadeshia H K D H., 2009, Stat Anal Data Min, V1, P296, DOI DOI 10.1002/SAM.10018
  • [14] Stalking the Materials Genome: A Data-Driven Approach to the Virtual Design of Nanostructured Polymers
    Breneman, Curt M.
    Brinson, L. Catherine
    Schadler, Linda S.
    Natarajan, Bharath
    Krein, Michael
    Wu, Ke
    Morkowchuk, Lisa
    Li, Yang
    Deng, Hua
    Xu, Hongyi
    [J]. ADVANCED FUNCTIONAL MATERIALS, 2013, 23 (46) : 5746 - 5752
  • [15] SOLID MIXTURE PERMITTIVITIES
    BROWN, WF
    [J]. JOURNAL OF CHEMICAL PHYSICS, 1955, 23 (08) : 1514 - 1517
  • [16] Engineering materials informatics
    Cebon, D.
    Ashby, M. F.
    [J]. MRS BULLETIN, 2006, 31 (12) : 1004 - 1012
  • [17] A data-driven approach to establishing microstructure-property relationships in porous transport layers of polymer electrolyte fuel cells
    Cecen, A.
    Fast, T.
    Kumbur, E. C.
    Kalidindi, S. R.
    [J]. JOURNAL OF POWER SOURCES, 2014, 245 : 144 - 153
  • [18] Chance S, 2016, ADV MATER PROCESS, V174, P25
  • [19] What are ontologies, and why do we need them?
    Chandrasekaran, B
    Josephson, JR
    Benjamins, VR
    [J]. IEEE INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 1999, 14 (01): : 20 - 26
  • [20] ThermoML-An XML-based approach for storage and exchange of experimental and critically evaluated thermophysical and thermochemical property data. 2. Uncertainties
    Chirico, RD
    Frenkel, M
    Diky, VV
    Marsh, KN
    Wilhoit, RC
    [J]. JOURNAL OF CHEMICAL AND ENGINEERING DATA, 2003, 48 (05) : 1344 - 1359