Data-driven Materials Selection

Data-Driven Materials Selection is a systematic methodology within sustainable materials selection that leverages empirical data, computational analytics, and predictive modeling to objectively prioritize materials based on performance, environmental impact, and lifecycle criteria, distinguishing it from heuristic or experience-based selection approaches.

90

Publications

5.8K

Citations

244

Authors

127

Institutions

Publications per year

2017–2026

28

Authors

244

  1. MF
    Michael F. Ashby

    University of Cambridge, United Kingdom

    4 publications · 548 citations

    4

    h-index

  2. DC
    David Cebon

    University of Cambridge, United Kingdom

    4 publications · 454 citations

    4

    h-index

  3. KE
    K.L. Edwards

    University of Derby, United Kingdom

    4 publications · 547 citations

    4

    h-index

  4. SC
    Shankar Chakraborty

    Jadavpur University, India

    3 publications · 494 citations

    3

    h-index

  5. MA
    MF Ashby

    University of Cambridge, United Kingdom

    3 publications · 40 citations

    3

    h-index

1–5 of 244

Venues

  1. Materials & Design (1980-2015)

    25 publications · 2.8K citations

    21

    h-index

  2. 4

    h-index

  3. Cambridge University Engineering Department Publications Database

    Repository · 3 publications · 40 citations

    3

    h-index

  4. Expert Systems with Applications

    2 publications · 43 citations

    2

    h-index

  5. Materials Science and Technology

    MST · 2 publications · 114 citations

    2

    h-index

1–5