Data-driven Material Design

Data-Driven Material Design is a systematic approach to material innovation that leverages empirical data and computational analysis to inform and optimize material properties and behaviors, distinguishing itself from traditional design methodologies through its reliance on data-derived insights rather than heuristic or intuition-based reasoning.

122

Publications

20.7K

Citations

615

Authors

232

Institutions

Publications per year

2017–2026

95

Authors

615

  1. WC
    Wei Chen

    Northwestern University, United States

    4 publications · 135 citations

    4

    h-index

  2. RA
    Raymundo Arróyave

    Texas A&M University, United States

    4 publications · 217 citations

    4

    h-index

  3. KR
    Krishna Rajan

    Iowa State University, United States

    3 publications · 406 citations

    3

    h-index

  4. KC
    Kamal Choudhary

    National Institute of Standards and Technology, United States

    3 publications · 246 citations

    3

    h-index

  5. SC
    Stefano Curtarolo

    Duke University, United States

    3 publications · 166 citations

    3

    h-index

1–5 of 615

Venues

  1. npj Computational Materials

    5 publications · 287 citations

    5

    h-index

  2. Materials Genome Engineering Advances

    3 publications · 194 citations

    3

    h-index

  3. 3

    h-index

  4. Journal of Materiomics

    3 publications · 418 citations

    3

    h-index

  5. Journal of Materials Informatics

    JMI · 3 publications · 79 citations

    3

    h-index

1–5