Candidate Material Discovery

Candidate Material Discovery is a systematic academic process within high-throughput materials screening that identifies novel materials with potential functional properties by distinguishing them from known or hypothetical substances through computational, experimental, or hybrid methodologies.

643

Publications

54.1K

Citations

2.7K

Authors

758

Institutions

Publications per year

2017–2026

439

Authors

2.7K

  1. JM
    John M. Gregoire

    California Institute of Technology, United States

    15 publications · 858 citations

    13

    h-index

  2. SK
    Santosh K. Suram

    California Institute of Technology, United States

    12 publications · 538 citations

    12

    h-index

  3. TL
    Turab Lookman

    Los Alamos National Laboratory, United States

    12 publications · 1.9K citations

    11

    h-index

  4. PV
    Prasanna V. Balachandran

    University of Virginia, United States

    10 publications · 1.6K citations

    10

    h-index

  5. BM
    Bryce Meredig

    Citrine Informatics (United States), United States

    9 publications · 4.2K citations

    9

    h-index

1–5 of 2.7K

Venues

  1. npj Computational Materials

    32 publications · 3.9K citations

    27

    h-index

  2. Chemistry of Materials

    20 publications · 2.9K citations

    17

    h-index

  3. Nature Communications

    14 publications · 2K citations

    14

    h-index

  4. Journal of the American Chemical Society

    JACS · 13 publications · 1.7K citations

    13

    h-index

  5. The Journal of Physical Chemistry Letters

    14 publications · 926 citations

    13

    h-index

1–5