World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
51
Citations
9385
World Ranking
3882
National Ranking
1130

John M. Gregoire publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where John M. Gregoire sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 198 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

John M. Gregoire D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where John M. Gregoire sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 51 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

John M. Gregoire is affiliated with the California Institute of Technology in the United States. Their research primarily focuses on materials science and energy, with significant contributions to materials chemistry and renewable energy, sustainability, and the environment.

Their work spans various subfields, including electrical and electronic engineering, catalysis, and information systems and management. Gregoire's research topics include:

  • Machine learning in materials science
  • Electrocatalysts for energy conversion
  • Advanced photocatalysis techniques
  • Electronic and structural properties of oxides
  • X-ray diffraction in crystallography
  • CO2 reduction techniques and catalysts
  • Copper-based nanomaterials and applications

Gregoire has published frequently in several key scientific venues, reflecting their interdisciplinary focus. These publication venues include:

  • Digital Discovery
  • arXiv (Cornell University)
  • ACS Energy Letters
  • Matter
  • Journal of Materials Chemistry A

Among the recent publications by Gregoire are notable contributions such as:

  • "Autonomous experimentation systems for materials development: A community perspective" (2021, Matter)
  • "Analysis of the limitations in the oxygen reduction activity of transition metal oxide surfaces" (2021, Nature Catalysis)
  • "High-throughput, combinatorial synthesis of multimetallic nanoclusters" (2020, Proceedings of the National Academy of Sciences)
  • "Benchmarking the acceleration of materials discovery by sequential learning" (2020, Chemical Science)
  • "The 2022 solar fuels roadmap" (2022, Journal of Physics D Applied Physics)

Frequent collaborators in Gregoire's research include Dan Guevarra, Lan Zhou, Joel A. Haber, Yungchieh Lai, and Kevin Kan. These coauthors have worked with Gregoire on a considerable number of publications, contributing to the breadth of research output.

Best Publications

  • Lithium-Assisted Plastic Deformation of Silicon Electrodes in Lithium-Ion Batteries: A First-Principles Theoretical Study

    Kejie Zhao;Wei L. Wang;John Gregoire;Matt Pharr

  • Inverse Design of Solid-State Materials via a Continuous Representation

    Juhwan Noh;Jaehoon Kim;Helge S. Stein;Benjamin Sanchez-Lengeling

  • The 2019 materials by design roadmap

    Kirstin Alberi;Marco Buongiorno Nardelli;Andriy Zakutayev;Lubos Mitas

  • The evolution of the polycrystalline copper surface, first to Cu(111) and then to Cu(100), at a fixed CO₂RR potential: a study by operando EC-STM.

    Youn-Geun Kim;Jack Hess Baricuatro;Alnald Javier;John Mathew Gregoire

  • Autonomous experimentation systems for materials development: A community perspective

    Eric Stach;Brian DeCost;A. Gilad Kusne;A. Gilad Kusne;Jason Hattrick-Simpers

  • Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

    M. L. Green;C. L. Choi;J. R. Hattrick-Simpers;A. M. Joshi

  • Analysis of the limitations in the oxygen reduction activity of transition metal oxide surfaces

    Hao Li;Sara Kelly;Dan Guevarra;Zhenbin Wang

  • Electrochemical Stability of Metastable Materials

    Arunima K. Singh;Lan Zhou;Aniketa Shinde;Santosh K. Suram

  • High-throughput, combinatorial synthesis of multimetallic nanoclusters

    Yonggang Yao;Zhennan Huang;Tangyuan Li;Hang Wang

  • Progress and prospects for accelerating materials science with automated and autonomous workflows

    Helge S Stein;John M Gregoire

  • Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment.

    Qimin Yan;Jie Yu;Santosh K. Suram;Lan Zhou

  • An Operando Investigation of (Ni–Fe–Co–Ce)Ox System as Highly Efficient Electrocatalyst for Oxygen Evolution Reaction

    Marco Favaro;Walter S. Drisdell;Matthew A. Marcus;John M. Gregoire

  • Discovering Ce-rich oxygen evolution catalysts, from high throughput screening to water electrolysis

    Joel A. Haber;Yun Cai;Suho Jung;Chengxiang Xiang

  • Robust and synthesizable photocatalysts for CO2 reduction: a data-driven materials discovery.

    Arunima K. Singh;Joseph H. Montoya;John M. Gregoire;Kristin A. Persson;Kristin A. Persson

  • High Throughput Light Absorber Discovery, Part 1: An Algorithm for Automated Tauc Analysis.

    Santosh K. Suram;Paul F. Newhouse;John M. Gregoire

  • The 2022 solar fuels roadmap

    Unknown

  • Scanning droplet cell for high throughput electrochemical and photoelectrochemical measurements

    John M. Gregoire;Chengxiang Xiang;Xiaonao Liu;Martin Marcin

  • Benchmarking the acceleration of materials discovery by sequential learning.

    Brian Rohr;Helge S. Stein;Dan Guevarra;Yu Wang

  • Rutile Alloys in the Mn-Sb-O System Stabilize Mn3+ to Enable Oxygen Evolution in Strong Acid

    Lan Zhou;Aniketa Shinde;Joseph H. Montoya;Arunima Singh

  • Machine learning of optical properties of materials – predicting spectra from images and images from spectra

    Helge S. Stein;Dan Guevarra;Paul F. Newhouse;Edwin Soedarmadji

  • Perspective: Composition–structure–property mapping in high-throughput experiments: Turning data into knowledge

    Jason R. Hattrick-Simpers;John M. Gregoire;A. Gilad Kusne;A. Gilad Kusne

Frequent Co-Authors

Carla P. Gomes
Carla P. Gomes Cornell University
Jeffrey B. Neaton
Jeffrey B. Neaton University of California, Berkeley
Kristin A. Persson
Kristin A. Persson Lawrence Berkeley National Laboratory
Chengxiang Xiang
Chengxiang Xiang California Institute of Technology
Francis J. DiSalvo
Francis J. DiSalvo Cornell University
Héctor D. Abruña
Héctor D. Abruña Cornell University
Francesca M. Toma
Francesca M. Toma Lawrence Berkeley National Laboratory
Bart Selman
Bart Selman Cornell University
Thomas F. Jaramillo
Thomas F. Jaramillo Stanford University
Junko Yano
Junko Yano Lawrence Berkeley National Laboratory

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