Publikationen von Matthias Scheffler

Lim, B.: Discussion, implementation and demonstration of AI-guided active workflows. Technische Universität Darmstadt

Oehlers, M.: Identifying exceptional data points in materials science using machine learning. Technische Universität Berlin

Ahmetcik, E.: Machine Learning of the Stability of Octet Binaries. Technische Universität Berlin

Kowalski, H.-H.: First-principles Study of Thermoelectric Magnesium Silicides with High-Throughput Techniques. Technische Universität Berlin

Müller, P.M.: Thermal Conductivities of Group IV and Group III-V Compound Semiconductors from First Principles. Technische Universität Berlin

Foppa, L. und M. Scheffler: Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups., im Druck.

Kokott, S., F. Merz, Y. Yao, C. Carbogno, M. Rossi, V. Havu, M. Rampp, M. Scheffler und V. Blum: Efficient All-electron Hybrid Density Functionals for Atomistic Simulations Beyond 10,000 Atoms., im Druck.

Boley, M., F. Luong, S. Teshuva, D.F. Schmidt, L. Foppa und M. Scheffler: From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery., im Druck.

Foppa, L. und M. Scheffler: Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance., im Druck.

Lu, S., L.M. Ghiringhelli, C. Carbogno, J. Wang und M. Scheffler: On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials., im Druck.

Speckhard, D., C. Carbogno, L.M. Ghiringhelli, S. Lubeck, M. Scheffler und C. Draxl: Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models., im Druck.

Gavini, V., S. Baroni, V. Blum, D.R. Bowler, A. Buccheri, J.R. Chelikowsky, S. Das, W. Dawson, P. Delugas, M. Dogan, C. Draxl, G. Galli, L. Genovese, P. Giannozzi, M. Giantomassi, X. Gonze, M. Govoni, A. Gulans, F. Gygi, J.M. Herbert, S. Kokott, T.D. Kühne, K.-H. Liou, T. Miyazaki, P. Motamarri, A. Nakata, J.E. Pask, C. Plessl, L.E. Ratcliff, R.M. Richard, M. Rossi, R. Schade, M. Scheffler, O. Schütt, P. Suryanarayana, M. Torrent, L. Truflandier, T.L. Windus, Q. Xu, V.W.-Z. Yu und D. Perez: Roadmap on Electronic Structure Codes in the Exascale Era., im Druck.

Boley, M. und M. Scheffler: Learning Rules for Materials Properties and Functions., im Druck.

Kloppenburg, J., L. Nemec, B. Lange, M. Scheffler und V. Blum: The (3×3)-SiC-(¯1¯1¯1) Reconstruction: Atomic Structure of the Graphene Precursor Surface from a Large-Scale First-Principles Structure Search., im Druck.

Mazheika, A., Y. Wang, R. Valero, L.M. Ghiringhelli, F. Vines, F. Illas, S.V. Levchenko und M. Scheffler: Ab initio data-analytics study of carbon-dioxide activation on semiconductor oxide surfaces., im Druck.

Acosta, C.M., R. Ouyang, A. Fazzio, M. Scheffler, L.M. Ghiringhelli und C. Carbogno: Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing., im Druck.

Ghiringhelli, L.M., C. Carbogno, S.V. Levchenko, F.R. Mohamed, G. Huhs, M. Lüders, M. Oliveira und M. Scheffler: Towards a Common Format for Computational Materials Science Data. (131), 1–16 (2016).

Nieminen, R.M., S. Bonella, L. Drury, M. Scheffler und E. Molinari: Three European Centers of Excellence in Computational Science. (133), 1–13 (2016).

Scheffler, M. und W.-D. Schneider: Focus on Advances in Surface and Interface Science. New Journal of Physics 9 (2007).

Ghiringhelli, L.M., C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C.T. Koch, M. Kühbach, A.N. Ladines, P. Lambrix, M.-O. Himmer, S.V. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G.-M. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll und M. Scheffler: Shared Metadata for Data-Centric Materials Science. Scientific Data 10, 626 (2023).