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Materials informatics

Author

Listed:
  • Seeram Ramakrishna

    (National University of Singapore, Institution of Engineers Singapore, and SPRING)

  • Tong-Yi Zhang

    (Materials Genome Institute (MGI), Shanghai University (SHU), and Shanghai Materials Genome Institute)

  • Wen-Cong Lu

    (Materials Genome Institute (MGI), Shanghai University (SHU), and Shanghai Materials Genome Institute)

  • Quan Qian

    (Materials Genome Institute (MGI), Shanghai University (SHU), and Shanghai Materials Genome Institute)

  • Jonathan Sze Choong Low

    (Singapore Institute of Manufacturing Technology, ASTAR)

  • Jeremy Heiarii Ronald Yune

    (Singapore Institute of Manufacturing Technology, ASTAR)

  • Daren Zong Loong Tan

    (Singapore Institute of Manufacturing Technology, ASTAR)

  • Stéphane Bressan

    (National University of Singapore)

  • Stefano Sanvito

    (Trinity College)

  • Surya R. Kalidindi

    (Georgia Institute of Technology)

Abstract

Materials informatics employs techniques, tools, and theories drawn from the emerging fields of data science, internet, computer science and engineering, and digital technologies to the materials science and engineering to accelerate materials, products and manufacturing innovations. Manufacturing is transforming into shorter design cycles, mass customization, on-demand production, and sustainable products. Additive manufacturing or 3D printing is a popular example of such a trend. However, the success of this manufacturing transformation is critically dependent on the availability of suitable materials and of data on invertible processing–structure–property–performance life cycle linkages of materials. Experience suggests that the material development cycle, i.e. the time to develop and deploy new material, generally exceeds the product design and development cycle. Hence, there is a need to accelerate materials innovation in order to keep up with product and manufacturing innovations. This is a major challenge considering the hundreds of thousands of materials and processes, and the huge amount of data on microstructure, composition, properties, and functional, environmental, and economic performance of materials. Moreover, the data sharing culture among the materials community is sparse. Materials informatics is key to the necessary transformation in product design and manufacturing. Through the association of material and information sciences, the emerging field of materials informatics proposes to computationally mine and analyze large ensembles of experimental and modeling datasets efficiently and cost effectively and to deliver core materials knowledge in user-friendly ways to the designers of materials and products, and to the manufacturers. This paper reviews the various developments in materials informatics and how it facilitates materials innovation by way of specific examples.

Suggested Citation

  • Seeram Ramakrishna & Tong-Yi Zhang & Wen-Cong Lu & Quan Qian & Jonathan Sze Choong Low & Jeremy Heiarii Ronald Yune & Daren Zong Loong Tan & Stéphane Bressan & Stefano Sanvito & Surya R. Kalidindi, 2019. "Materials informatics," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2307-2326, August.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:6:d:10.1007_s10845-018-1392-0
    DOI: 10.1007/s10845-018-1392-0
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    References listed on IDEAS

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    1. Dezhen Xue & Prasanna V. Balachandran & John Hogden & James Theiler & Deqing Xue & Turab Lookman, 2016. "Accelerated search for materials with targeted properties by adaptive design," Nature Communications, Nature, vol. 7(1), pages 1-9, September.
    2. Paul Raccuglia & Katherine C. Elbert & Philip D. F. Adler & Casey Falk & Malia B. Wenny & Aurelio Mollo & Matthias Zeller & Sorelle A. Friedler & Joshua Schrier & Alexander J. Norquist, 2016. "Machine-learning-assisted materials discovery using failed experiments," Nature, Nature, vol. 533(7601), pages 73-76, May.
    3. Gabriel B. Grant & Thomas P. Seager & Guillaume Massard & Loring Nies, 2010. "Information and Communication Technology for Industrial Symbiosis," Journal of Industrial Ecology, Yale University, vol. 14(5), pages 740-753, October.
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