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Materials Science

D-Index
82
Citations
30040
World Ranking
2441
National Ranking
705

Chemistry

D-Index
81
Citations
27499
World Ranking
3199
National Ranking
1064

Overview

Dane Morgan is affiliated with the University of Wisconsin-Madison in the United States. Their research spans multiple areas primarily within materials science and engineering, with a significant focus on the applications of machine learning in materials research.

The scientist's main fields of study include:

  • Materials Science
  • Engineering

Within these broader fields, their subfields of research extend into:

  • Materials Chemistry
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Surfaces, Coatings and Films
  • Biomedical Engineering

Their work addresses a range of topics, reflecting a specialized focus on materials and computational methods:

  • Machine Learning in Materials Science
  • Semiconductor materials and devices
  • Electron and X-Ray Spectroscopy Techniques
  • Electronic and Structural Properties of Oxides
  • Nuclear Materials and Properties
  • Advancements in Solid Oxide Fuel Cells
  • Material Dynamics and Properties

Their frequent publication venues illustrate their engagement with both computational methods and material characterization:

  • arXiv (Cornell University)
  • Microscopy and Microanalysis
  • Computational Materials Science
  • ECS Meeting Abstracts
  • Journal of Nuclear Materials

Among notable papers associated with the scientist, these represent a selection highlighting recent work and impact:

  • "Machine learning in nuclear materials research," 2022, Current Opinion in Solid State and Materials Science
  • "Extracting accurate materials data from research papers with conversational language models and prompt engineering," 2024, Nature Communications
  • "Electronic Structure-Based Descriptors for Oxide Properties and Functions," 2022, Accounts of Chemical Research
  • "Work Function: Fundamentals, Measurement, Calculation, Engineering, and Applications," 2023, Physical Review Applied
  • "Radiation-induced segregation in a ceramic," 2020, Nature Materials

The scientist collaborates extensively with colleagues, with frequent co-authorship from:

  • Ryan Jacobs
  • John H. Booske
  • Izabela Szlufarska
  • Paul M. Voyles
  • Maciej P. Polak

Best Publications

  • First-principles study of native point defects in ZnO

    A. F. Kohan;G. Ceder;D. Morgan;Chris G. Van de Walle

  • AFLOW: An automatic framework for high-throughput materials discovery

    Stefano Curtarolo;Wahyu Setyawan;Gus L Hart;Michal Jahnatek

  • LI CONDUCTIVITY IN LIX MPO 4 ( M = MN , FE , CO , NI ) OLIVINE MATERIALS

    D Morgan;A J Van Der Ven;G Ceder

  • Instability of Pt ∕ C Electrocatalysts in Proton Exchange Membrane Fuel Cells A Mechanistic Investigation

    P. J. Ferreira;Y. Shao-Horn;D. Morgan

  • First-principles prediction of redox potentials in transition-metal compounds with LDA+ U

    Fei Zhou;Matteo Cococcioni;Chris A. Marianetti;Dane Morgan

  • Instability of Supported Platinum Nanoparticles in Low-Temperature Fuel Cells

    Y. Shao-Horn;W. C. Sheng;S. Chen;Paulo J Ferreira

  • Prediction of solid oxide fuel cell cathode activity with first-principles descriptors

    Yueh-Lin Lee;Jesper Kleis;Jan Rossmeisl;Yang Shao-Horn

  • Ab initio energetics of LaBO3(001) (B=Mn, Fe, Co, and Ni) for solid oxide fuel cell cathodes

    Yueh-Lin Lee;Jesper Kleis;Jan Rossmeisl;Dane Morgan

  • Predicting crystal structure by merging data mining with quantum mechanics.

    Christopher C. Fischer;Kevin J. Tibbetts;Dane Morgan;Gerbrand Ceder

  • The electronic structure and band gap of LiFePO4 and LiMnPO4

    Fei Zhou;Kisuk Kang;Thomas Maxisch;Gerbrand Ceder

  • New frontiers for the materials genome initiative

    Juan J. de Pablo;Nicholas E. Jackson;Michael A. Webb;Long Qing Chen

  • Predicting crystal structures with data mining of quantum calculations.

    Stefano Curtarolo;Dane Morgan;Kristin Persson;John Rodgers

  • Accuracy of ab initio methods in predicting the crystal structures of metals: A review of 80 binary alloys

    Stefano Curtarolo;Dane Morgan;Gerbrand Ceder

  • Pt nanoparticle stability in PEM fuel cells: influence of particle size distribution and crossover hydrogen

    Edward F. Holby;Wenchao Sheng;Yang Shao-Horn;Dane Morgan

  • Opportunities and Challenges for Machine Learning in Materials Science

    Dane Morgan;Ryan Jacobs

  • Surface strontium enrichment on highly active perovskites for oxygen electrocatalysis in solid oxide fuel cells

    Ethan J. Crumlin;Eva Mutoro;Zhi Liu;Michael E. Grass

  • Nondilute diffusion from first principles: Li diffusion in Li x TiS 2

    Anton Van der Ven;John C. Thomas;Qingchuan Xu;Benjamin Swoboda

  • Electrochemical modeling of intercalation processes with phase field models

    B.C. Han;A. Van der Ven;D. Morgan;G. Ceder

  • First-principles study of the stability and electronic structure of metal hydrides

    H. Smithson;H. Smithson;C. A. Marianetti;D. Morgan;A. Van der Ven

  • Phase Stability of Nickel Hydroxides and Oxyhydroxides

    A. Van der Ven;D. Morgan;Y. S. Meng;G. Ceder

  • Towards more accurate First Principles prediction of redox potentials in transition-metal compounds with LDA+U

    Fei Zhou;Matteo Cococcioni;Chris A. Marianetti;Dane Morgan

Frequent Co-Authors

Gerbrand Ceder
Gerbrand Ceder University of California, Berkeley
John H. Booske
John H. Booske University of Wisconsin–Madison
Paul M. Voyles
Paul M. Voyles University of Wisconsin–Madison
Thomas F. Kuech
Thomas F. Kuech University of Wisconsin–Madison
Stefano Curtarolo
Stefano Curtarolo Duke University
Chris Wolverton
Chris Wolverton Northwestern University
Brian D. Wirth
Brian D. Wirth University of Tennessee at Knoxville
Kristin A. Persson
Kristin A. Persson Lawrence Berkeley National Laboratory
Michael D. Biegalski
Michael D. Biegalski Oak Ridge National Laboratory

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