World's Best Scientists 2026 revealed!

D-Index & Metrics

Materials Science

D-Index
128
Citations
66853
World Ranking
372
National Ranking
142

Chemistry

D-Index
122
Citations
63039
World Ranking
449
National Ranking
192

Chris Wolverton publication distribution in Materials Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Materials Science in 2026. The highlighted bar marks where Chris Wolverton sits on this spectrum.

50–69 publications: 28 scientists 70–89 publications: 152 scientists 90–109 publications: 356 scientists 110–129 publications: 487 scientists 130–149 publications: 723 scientists 150–169 publications: 835 scientists 170–189 publications: 850 scientists 190–209 publications: 891 scientists 210–229 publications: 862 scientists 230–249 publications: 766 scientists 250–269 publications: 726 scientists 270–289 publications: 665 scientists 290–309 publications: 593 scientists 310–329 publications: 537 scientists 330–349 publications: 477 scientists 350–369 publications: 440 scientists 370–389 publications: 356 scientists 390–409 publications: 321 scientists 410–429 publications: 256 scientists 430–449 publications: 246 scientists 450–469 publications: 216 scientists 470–489 publications: 212 scientists 490–509 publications: 174 scientists 510–529 publications: 194 scientists 530–549 publications: 162 scientists 550–569 publications: 131 scientists 570–589 publications: 111 scientists 590–609 publications: 103 scientists 610–629 publications: 99 scientists 630–649 publications: 77 scientists 650–669 publications: 92 scientists 670–689 publications: 56 scientists 690–709 publications: 53 scientists 710–729 publications: 53 scientists 730–749 publications: 38 scientists 750–769 publications: 52 scientists 770–789 publications: 43 scientists 790–809 publications: 38 scientists 810–829 publications: 34 scientists 830–849 publications: 25 scientists 850–869 publications: 18 scientists 870–889 publications: 20 scientists 890–909 publications: 24 scientists 910–929 publications: 27 scientists 930–949 publications: 20 scientists 950–969 publications: 17 scientists 970–989 publications: 10 scientists 990–1,009 publications: 16 scientists 1,010–1,029 publications: 13 scientists 1,030–1,049 publications: 12 scientists 1,050–1,069 publications: 9 scientists 1,070–1,089 publications: 8 scientists 1,090–1,109 publications: 7 scientists 1,110–1,129 publications: 9 scientists 1,130–1,149 publications: 2 scientists 1,150–1,162 publications: 5 scientists 1,163+ publications: 100 scientists
50 publications 1,163+

This scientist: 720 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,163 publications or more.

Chris Wolverton D-index placement in Materials Science in 2026

The chart shows the D-index (discipline H-index) distribution of Materials Science scientists ranked by Research.com in 2026. The highlighted bar marks where Chris Wolverton sits on this spectrum.

40–41 D-Index: 211 scientists 42–43 D-Index: 450 scientists 44–45 D-Index: 612 scientists 46–47 D-Index: 612 scientists 48–49 D-Index: 598 scientists 50–51 D-Index: 657 scientists 52–53 D-Index: 667 scientists 54–55 D-Index: 621 scientists 56–57 D-Index: 597 scientists 58–59 D-Index: 610 scientists 60–61 D-Index: 587 scientists 62–63 D-Index: 606 scientists 64–65 D-Index: 533 scientists 66–67 D-Index: 490 scientists 68–69 D-Index: 469 scientists 70–71 D-Index: 378 scientists 72–73 D-Index: 421 scientists 74–75 D-Index: 359 scientists 76–77 D-Index: 323 scientists 78–79 D-Index: 299 scientists 80–81 D-Index: 230 scientists 82–83 D-Index: 210 scientists 84–85 D-Index: 195 scientists 86–87 D-Index: 203 scientists 88–89 D-Index: 175 scientists 90–91 D-Index: 175 scientists 92–93 D-Index: 142 scientists 94–95 D-Index: 121 scientists 96–97 D-Index: 117 scientists 98–99 D-Index: 107 scientists 100–101 D-Index: 88 scientists 102–103 D-Index: 85 scientists 104–105 D-Index: 68 scientists 106–107 D-Index: 62 scientists 108–109 D-Index: 57 scientists 110–111 D-Index: 45 scientists 112–113 D-Index: 49 scientists 114–115 D-Index: 50 scientists 116–117 D-Index: 34 scientists 118–119 D-Index: 38 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 28 scientists 126–127 D-Index: 24 scientists 128–129 D-Index: 33 scientists 130–131 D-Index: 28 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 20 scientists 136–137 D-Index: 23 scientists 138–139 D-Index: 17 scientists 140–141 D-Index: 12 scientists 142–143 D-Index: 17 scientists 144–145 D-Index: 21 scientists 146–147 D-Index: 13 scientists 148–149 D-Index: 11 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 13 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 4 scientists 162–163 D-Index: 4 scientists 164 D-Index: 3 scientists 165+ D-Index: 98 scientists
40 D-Index 165+

This scientist: 128 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 165 D-Index or more.

Research.com Recognitions

  • 2018 - ASM Fellow “For innovative development and use of first principle atomistic and multi-scale computational 

Overview

Chris Wolverton is affiliated with Northwestern University in the United States and has contributed extensively to research in materials science. Their work spans a broad range of topics within this field, with significant focus on materials chemistry and related subfields.

Their recent publications include:

  • Recent advances and applications of deep learning methods in materials science, 2022, npj Computational Materials
  • Electronic-structure methods for materials design, 2021, Nature Materials
  • Particlelike Phonon Propagation Dominates Ultralow Lattice Thermal Conductivity in Crystalline Tl3VSe4, 2020, Physical Review Letters
  • High Thermoelectric Performance in the New Cubic Semiconductor AgSnSbSe3 by High-Entropy Engineering, 2020, Journal of the American Chemical Society
  • High-Throughput Study of Lattice Thermal Conductivity in Binary Rocksalt and Zinc Blende Compounds Including Higher-Order Anharmonicity, 2020, Physical Review X

The frequent coauthors collaborating with Chris Wolverton include:

  • Sean D. Griesemer
  • Logan Ward
  • Mercouri G. Kanatzidis
  • Jiahong Shen
  • Yi Xia

The scientist's contributions have been published across several venues, notably:

  • The Cambridge Structural Database
  • Chemistry of Materials
  • arXiv (Cornell University)
  • Journal of the American Chemical Society
  • npj Computational Materials

Chris Wolverton's main field of study is Materials Science, with a particular emphasis on:

  • Materials Chemistry
  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering
  • Inorganic Chemistry
  • Biomedical Engineering

The primary topics of their research include:

  • X-ray Diffraction in Crystallography
  • Crystallization and Solubility Studies
  • Machine Learning in Materials Science
  • Advanced Thermoelectric Materials and Devices
  • Thermal properties of materials
  • Electronic and Structural Properties of Oxides
  • Inorganic Chemistry and Materials

In recognition of their work, Chris Wolverton was awarded the ASM Fellow in 2018 for innovative development and use of first principle atomistic and multi-scale computational methods.

Best Publications

  • Ultralow thermal conductivity and high thermoelectric figure of merit in SnSe crystals

    Li Dong Zhao;Shih Han Lo;Yongsheng Zhang;Hui Sun

  • Electrical energy storage for transportation—approaching the limits of, and going beyond, lithium-ion batteries

    Michael M. Thackeray;Christopher Wolverton;Eric D. Isaacs

  • Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

    James E. Saal;Scott Kirklin;Muratahan Aykol;Bryce Meredig

  • The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies

    Scott Kirklin;J. E. Saal;Bryce Meredig;A. Thompson

  • Ultrahigh power factor and thermoelectric performance in hole-doped single-crystal SnSe

    Li Dong Zhao;Li Dong Zhao;Gangjian Tan;Shiqiang Hao;Jiaqing He

  • A general-purpose machine learning framework for predicting properties of inorganic materials

    Logan Ward;Ankit Agrawal;Alok Nidhi Choudhary;Christopher M Wolverton

  • High capacity hydrogen storage materials: attributes for automotive applications and techniques for materials discovery

    Jun Jun Yang;Andrea C Sudik;Christopher Wolverton;Donald J. Siegel

  • Recent Advances and Applications of Deep Learning Methods in Materials Science

    Kamal Choudhary;Brian DeCost;Chi Chen;Anubhav Jain

  • All-scale hierarchical thermoelectrics: MgTe in PbTe facilitates valence band convergence and suppresses bipolar thermal transport for high performance

    L. D. Zhao;H. J. Wu;S. Q. Hao;C. I. Wu

  • Combinatorial screening for new materials in unconstrained composition space with machine learning

    Bryce Meredig;Amit K Agrawal;Scott Kirklin;James E. Saal

  • High Thermoelectric Performance of p-Type SnTe via a Synergistic Band Engineering and Nanostructuring Approach

    Gangjian Tan;Li Dong Zhao;Fengyuan Shi;Jeff W. Doak

  • Non-equilibrium processing leads to record high thermoelectric figure of merit in PbTe-SrTe.

    Gangjian Tan;Fengyuan Shi;Shiqiang Hao;Li Dong Zhao;Li Dong Zhao

  • Gravity-regulated differential auxin transport from columella to lateral root cap cells

    Iris Ottenschläger;Patricia Wolff;Chris Wolverton;Rishikesh P. Bhalerao

  • Crystal structure and stability of complex precipitate phases in Al–Cu–Mg–(Si) and Al–Zn–Mg alloys

    C. Wolverton

  • Developing an improved crystal graph convolutional neural network framework for accelerated materials discovery

    Cheol Woo Park;Chris Wolverton

  • Codoping in SnTe: Enhancement of Thermoelectric Performance through Synergy of Resonance Levels and Band Convergence

    Gangjian Tan;Fengyuan Shi;Shiqiang Hao;Hang Chi

  • High-throughput DFT calculations of formation energy, stability and oxygen vacancy formation energy of ABO 3 perovskites.

    Antoine A. Emery;Chris Wolverton

  • ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition.

    Dipendra Jha;Logan Ward;Arindam Paul;Wei-Keng Liao

  • Solute-vacancy binding in aluminum

    C. Wolverton

  • Toward Computational Materials Design: The Impact of Density Functional Theory on Materials Research

    Jürgen Hafner;Christopher Wolverton;Gerbrand Ceder

  • High thermoelectric performance via hierarchical compositionally alloyed nanostructures

    Li Dong Zhao;Shiqiang Hao;Shih Han Lo;Chun I. Wu

  • First-principles study of crystal structure and stability of Al-Mg-Si-(Cu) precipitates

    C. Ravi;C. Ravi;C. Wolverton

  • Forward for Symposium “Approaches for Investigating Phase Transformations at the Atomic Scale

    Neal D. Evans;Neal D. Evans;Francisca Caballero;Christopher M Wolverton;David N Seidman

Frequent Co-Authors

Vinayak P. Dravid
Vinayak P. Dravid Northwestern University
Mercouri G. Kanatzidis
Mercouri G. Kanatzidis Northwestern University
Ctirad Uher
Ctirad Uher University of Michigan–Ann Arbor
D. de Fontaine
D. de Fontaine University of California, Berkeley
Alex Zunger
Alex Zunger University of Colorado Boulder
Gangjian Tan
Gangjian Tan Wuhan University of Technology
Li-Dong Zhao
Li-Dong Zhao Beihang University
Michael M. Thackeray
Michael M. Thackeray Argonne National Laboratory
Xianli Su
Xianli Su Wuhan University of Technology
G. Jeffrey Snyder
G. Jeffrey Snyder Northwestern University

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