Publikationen von Thomas Purcell

Bauer, S.; Benner, P.; Bereau, T.; Blum, V.; Boley, M.; Carbogno, C.; Catlow, C. R. A.; Dehm, G.; Eibl, S.; Ernstorfer, R. et al.; Fekete, A.; Foppa, L.; Fratzl, P.; Freysoldt, C.; Gault, B.; Ghiringhelli, L. M.; Giri, S. K.; Gladyshev, A.; Goyal, P.; Hattrick-Simpers, J.; Kabalan, L.; Karpov, P.; Khorrami, M. S.; Koch, C.; Kokott, S.; Kosch, T.; Kowalec, I.; Kremer, K.; Leitherer, A.; Li, Y.; Liebscher, C. H.; Logsdail, A. J.; Lu, Z.; Luong, F.; Marek, A.; Merz, F.; Mianroodi, J. R.; Neugebauer, J.; Pei, Z.; Purcell, T.; Raabe, D.; Rampp, M.; Rossi, M.; Rost, J.-M.; Saal, J. E.; Saalmann, U.; Sasidhar, K. N.; Saxena, A.; Sbailo, L.; Scheidgen, M.; Schloz, M.; Schmidt, D. F.; Teshuva, S.; Trunschke, A.; Wei, Y.; Weikum, G.; Xian, R. P.; Yao, Y.; Yin, J.; Zhao, M.; Scheffler, M.: Roadmap on data-centric materials science. Modelling and Simulation in Materials Science and Engineering 32 (6), 063301 (2024)

Dean, J.; Scheffler, M.; Purcell, T.; Barabash, S. V.; Bhowmik, R.; Bazhirov, T.: Interpretable Machine Learning for Materials Design. Journal of Materials Research 38 (20), S. 4477 - 4496 (2023)

Purcell, T.; Scheffler, M.; Ghiringhelli, L. M.: Recent advances in the SISSO method and their implementation in the SISSO++ Code. The Journal of Chemical Physics 159 (11), 114110 (2023)

Purcell, T.; Scheffler, M.; Ghiringhelli, L. M.; Carbogno, C.: Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence. npj Computational Materials 9, 112 (2023)

Knoop, F.; Purcell, T.; Scheffler, M.; Carbogno, C.: Anharmonicity in Thermal Insulators: An Analysis from First Principles. Physical Review Letters 130 (23), 236301 (2023)

Foppa, L.; Purcell, T.; Levchenko, S. V.; Scheffler, M.; Ghiringhelli, L. M.: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites. Physical Review Letters 129 (5), 0545301 (2022)

Purcell, T.; Scheffler, M.; Carbogno, C.; Ghiringhelli, L. M.: SISSO++: A C++ Implementation of the Sure-Independence Screening and Sparisifying Operator Approach. The Journal of Open Source Software 7 (71), 3960 (2022)

Andersen, C. W.; Armiento, R.; Blokhin, E.; Conduit, G. J.; Dwaraknath, S.; Evans, M. L.; Fekete, Á.; Gopakumar, A.; Gražulis, S.; Merkys, A. et al.; Mohamed, F. R.; Oses, C.; Pizzi, G.; Rignanese, G.-M.; Scheidgen, M.; Talirz, L.; Toher, C.; Winston, D.; Aversa, R.; Choudhary, K.; Colinet, P.; Curtarolo, S.; Di Stefano, D.; Draxl, C.; Er, S.; Esters, M.; Fornari, M.; Giantomassi, M.; Govoni, M.; Hautier, G.; Hegde, V.; Horton, M. K.; Huck, P.; Huhs, G.; Hummelshøj, J.; Kariryaa, A.; Kozinsky, B.; Kumbhar, S.; Liu, M.; Marzari, N.; Morris, A. J.; Mostofi, A. A.; Persson, K. A.; Petretto, G.; Purcell, T.; Ricci, F.; Rose, F.; Scheffler, M.; Speckhard, D.; Uhrin, M.; Vaitkus, A.; Villars, P.; Waroquiers, D.; Wolverton, C.; Wu, M.; Yang, X.: OPTIMADE, an API for exchanging materials data. Scientific Data 8, 217 (2021)

Knoop, F.; Purcell, T.; Scheffler, M.; Carbogno, C.: FHI-vibes: Ab Initio Vibrational Simulations. The Journal of Open Source Software 5 (56), 2671 (2020)

Knoop, F.; Purcell, T.; Scheffler, M.; Carbogno, C.: Anharmonicity measure for materials. Physical Review Materials 4 (8), 083809 (2020)

Lenz, M.-O.; Purcell, T.; Hicks, D.; Curtarolo, S.; Scheffler, M.; Carbogno, C.: Parametrically constrained geometry relaxations for high-throughput materials science. npj Computational Materials 5, 123 (2019)

Purcell, T.: Recent Advances in the SISSO Method and Their Implementation in the SISSO++ Code. NOMAD Workshop on Data-centric Cruising for New and Novel Materials, Mechanisms, and Insights, Kiel, Germany (2023)

Purcell, T.: Accelerating the High-Throughput Search for New Thermal Insulators. School on Artificial Intelligence for Materials Science in the Exascale Era, Calonge, Spain (2023)

Purcell, T.: Symbolic Regression and Explainable AI. School on Artificial Intelligence for Materials Science in the Exascale Era, Calonge, Spain (2023)

Purcell, T.: Accelerating the High-Throughput Search for New Thermal Insulators. CBC Special Departmental Seminar, University of Arizona, Tucson, AZ, USA (2023)

Purcell, T.: AI Accelerated Workflows for Finding Thermal Insulators. NOMAD Meeting, Revealing New and Novel Materials, Mechanisms, and Insights (a Perspective), Potsdam, Germany (2022)

Purcell, T.: Accelerating the High-Throughput Search for New Thermal Insulators With Symbolic Regression. Overcoming the Global Energy Crisis by Materials Research Regional Series III, Georgia Institute of Technology, Atlanta, GA, USA (2022)

Purcell, T.: Machine-Learning Aided Approaches. Workshop, Capturing Anharmonic Vibrational Motion in First-Principles Simulations, Centre Européen de Calcul Atomique et Moléculaire (CECAM), Online Event (2021)

Kang, K.; Scheffler, M.; Carbogno, C.; Purcell, T.: Accelerating the Training and Improving the Reliability of Machine-Learned Interatomic Potentials for Strongly Anharmonic Materials Through Active Learning. (2024)