Person

Dr. Thomas 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

2023

Articles

1. J. Dean, M. Scheffler, T. A. R. Purcell, S. V. Barabash, R. Bhowmik, T. Bazhirov,
   Interpretable Machine Learning for Materials Design.
   Journal of Materials Research (2023)
   Download: pdf

2. F. Knoop, T. A. R. Purcell, M. Scheffler, and C. Carbogno,
   Anharmonicity in Thermal Insulators – An Analysis from First Principles.
   Phys. Rev. Lett. 130, 236301 (2023)
   Download: pdf

3. T. A. R. 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.
   npj Computational Materials 9 (1), 112 (2023)
   Download: pdf

4. T. A. R. Purcell, M. Scheffler, L. M. Ghiringhelli,
   Recent advances in the SISSO method and their implementation in the SISSO++ code.
   J. Chem. Phys. 159, 114110 (2023)
   Download (2023): pdf

2022

Articles

1. 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

2. T. A. R. 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

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. A. R. 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

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

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