FHI
The NOMAD Laboratory

Novel Materials Discovery at the FHI of the Max-Planck-Gesellschaft
and IRIS-Adlershof of the Humboldt-Universität zu Berlin

Learn More About Us

Home

NOMAD Members

Previous Members

FHI Phone List

Publications

Scientific Movies

Research

Worldwide Collaborations

Events

Seminars@FHI

Official Coffee

Co-organized Conferences

Library @FHI

FHI Library

Infos & Services

Info for New Members

IT Infrastructure

Responsibilities

Photo Albums

IMPRS Research School

Open Positions

How to get here

Contact

 

Data Protection

 

Person

Dr. Thomas Purcell

Purcell

Member since 08/2018
Phone: +49 30 8413 4853
Room: T 1.10
Email: purcell@fhi.mpg.de

RESEARCH TOPICS

RESEARCH GROUP: Artificial Intelligence-Assisted Discovery of Thermoelectric Materials 

Thermoelectric materials prediction 

METHODS

  • Density Functional Theory
  • Ab initio molecular dynamics
  • Compressed sensingmachine learning

2022

Articles

  1. J. Dean, M. Scheffler, T. A. R. Purcell, S. V. Barabash, R. Bhowmik, T. Bazhirov,
    Interpretable Machine Learning for Materials Design.
    Preprint Download: arXiv
  2. L. Foppa, T. A. R. Purcell, S. V. Levchenko, M. Scheffler, and L. M. Ghiringhelli,
    Hierarchical symbolic regression for identifying key physical parameters correlated with bulk properties of perovskites .
    Physical Review Letters 129, 55301 (2022); https://doi.org/10.1103/PhysRevLett.129.055301
    Download: pdf
  3. F. Knoop, T.A.R. Purcell, M. Scheffler, and C. Carbogno,
    Anharmonicity in Thermal Insulators – An Analysis from First Principles.
    (submitted)
    Preprint Download: arXiv
  4. T. Purcell, M. Scheffler, C. Carbogno, and L.M. Ghiringhelli,
    SISSO++: A C++ Implementation of the Sure-Independence Screening and Sparsifying Operator Approach.
    Journal of Open Source Software 7 (71), 3960 (2022); https://doi.org/10.21105/joss.03960
    Download: pdf
  5. T. Purcell, M. Scheffler, L. M. Ghiringhelli, C. Carbogno,
    Accelerating Materials-Space Exploration by Mapping Materials Properties via Artificial Intelligence: The Case of the Lattice Thermal Conductivity.
    Preprint Download: arXiv

2021

Articles

  1. C. W. Andersen, R. Armiento, E. Blokhin, G. J. Conduit, S. Dwaraknath, M. L. Evans, Á. Fekete, A. Gopakumar, S. Gražulis, A. Merkys, F. Mohamed, C. Oses, G. Pizzi, G.-M. Rignanese, M. Scheidgen, L. Talirz, C. Toher, D. Winston, R. Aversa, K. Choudhary, P. Colinet, S. Curtarolo, D. Di Stefano, C. Draxl, S. Er, M. Esters, M. Fornari, M. Giantomassi, M. Govoni, G. Hautier, V. Hegde, M. K. Horton, P. Huck, G. Huhs, J. Hummelshøj, A. Kariryaa, B. Kozinsky, S. Kumbhar, M. Liu, N. Marzari, A. J. Morris, A. Mostofi, K. A. Persson, G. Petretto, T. Purcell, F. Ricci, F. Rose, M. Scheffler, D. Speckhard, M. Uhrin, A. Vaitkus, P. Villars, D. Waroquiers, C. Wolverton, M. Wu, and X. Yang,
    OPTIMADE: an API for exchanging materials data.
    Scientific Data 8, 217 (2021); https://doi.org/10.1038/s41597-021-00974-z
    Download: pdf
  2. T. Esat, M. Knol, P. Leinen, M.F.B. Green, M. Esders, N. Friedrich, M. Maiworm, N. Ferri, P. Chmielniak, S. Sarwar, T. Deilmann, P. Krüger, H.H. Arefi, D. Corken, J. Gardner, K.T. Schütt, J. Rawson, P. Kögerler, M. Rohlfing, R. Findeisen, A. Tkatchenko, K.-R. Müller, R.J. Maurer, C. Wagner, R. Temirov and F.S. Tautz,
    A standing molecule as a coherent single-electron field emitter.
    In: 34th International Vacuum Nanoelectronics Conference (IVNC). (Eds.): S. Purcell and J.-P. Mazellier. IEEE, , 52–53 (2021). ISBN 978-1-6654-2589-6; https://doi.org/10.1109/IVNC52431.2021.9600722
    Download: pdf

2020

Articles

  1. F. Knoop, T.A.R. Purcell, M. Scheffler, and C. Carbogno,
    Anharmonicity Measure for Materials. Phys. Rev. Materials 4, 083809 (2020); https://doi.org/10.1103/PhysRevMaterials.4.083809
    Reprint download: pdf, Arxiv
  2. F. Knoop, T.A.R. Purcell, M. Scheffler, and C. Carbogno,
    FHI-vibes: Ab Initio Vibrational Simulations. J. Open Source Softw. 52, 2601 (2020); https://doi.org/10.21105/joss.02671
    Reprint download: pdf

2019

Articles

  1. M.-O. Lenz, T.A.R. Purcell, D. Hicks, S. Curtarolo, M. Scheffler, C. Carbogno,
    Parametrically constrained geometry relaxations for high-throughput materials science. npj Computational Materials 5, 123 (2019); https://doi.org/10.1038/s41524-019-0254-4
    Reprint download: pdf

Within the publication lists the label [abs,src,ps] links to abstract, source file, and postscript version of the respective paper on the e-print archives of xxx.lanl.gov. Source and postscript files are usually transfered as gz-compressed tar-files. If your browser cannot automatically unpack those files you should proceed as follows:

Save the file as paper.tar.gz Execute the following commands (on a UNIX machine): gunzip paper.tar.gz tar -xvf paper.tar

return