Publications of Matthias Scheffler

Thesis - PhD (37)

861.
Thesis - PhD
Scheffler, M.: Winkelaufgelöste Photoemission von Adsorbatsystemen. Technische Universität Berlin Berlin

Thesis - Diploma (1)

862.
Thesis - Diploma
Cao, J.: Polymerization of Carbon Nitride - experimental and theoretical investigation. Freie Universität Berlin

Thesis - Master (5)

863.
Thesis - Master
Zhao, B.: Identifying descriptors for the in-silico, high-throughput discovery of the thermal insulators for thermoelectric applications. Technische Universität Darmstadt
864.
Thesis - Master
Lim, B.: Discussion, implementation and demonstration of AI-guided active workflows. Technische Universität Darmstadt
865.
Thesis - Master
Oehlers, M.: Identifying exceptional data points in materials science using machine learning. Technische Universität Berlin
866.
Thesis - Master
Kowalski, H.-H.: First-principles Study of Thermoelectric Magnesium Silicides with High-Throughput Techniques. Technische Universität Berlin
867.
Thesis - Master
Ahmetcik, E.: Machine Learning of the Stability of Octet Binaries. Technische Universität Berlin

Thesis - Bachelor (1)

868.
Thesis - Bachelor
Müller, P.M.: Thermal Conductivities of Group IV and Group III-V Compound Semiconductors from First Principles. Technische Universität Berlin

Working Paper (11)

869.
Working Paper
Foppa, L. and M. Scheffler: Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups., in press.
870.
Working Paper
Kokott, S., F. Merz, Y. Yao, C. Carbogno, M. Rossi, V. Havu, M. Rampp, M. Scheffler and V. Blum: Efficient All-electron Hybrid Density Functionals for Atomistic Simulations Beyond 10,000 Atoms., in press.
871.
Working Paper
Boley, M., F. Luong, S. Teshuva, D.F. Schmidt, L. Foppa and M. Scheffler: From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery., in press.
872.
Working Paper
Foppa, L. and M. Scheffler: Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance., in press.
873.
Working Paper
Lu, S., L.M. Ghiringhelli, C. Carbogno, J. Wang and M. Scheffler: On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials., in press.
874.
Working Paper
Speckhard, D., C. Carbogno, L.M. Ghiringhelli, S. Lubeck, M. Scheffler and C. Draxl: Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models., in press.
875.
Working Paper
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 and D. Perez: Roadmap on Electronic Structure Codes in the Exascale Era., in press.
876.
Working Paper
Boley, M. and M. Scheffler: Learning Rules for Materials Properties and Functions., in press.
877.
Working Paper
Acosta, C.M., R. Ouyang, A. Fazzio, M. Scheffler, L.M. Ghiringhelli and C. Carbogno: Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing., in press.
878.
Working Paper
Nieminen, R.M., S. Bonella, L. Drury, M. Scheffler and E. Molinari: Three European Centers of Excellence in Computational Science. (133), 1–13 (2016).
879.
Working Paper
Ghiringhelli, L.M., C. Carbogno, S.V. Levchenko, F.R. Mohamed, G. Huhs, M. Lüders, M. Oliveira and M. Scheffler: Towards a Common Format for Computational Materials Science Data. (131), 1–16 (2016).

Issue (1)

880.
Issue
Scheffler, M. and W.-D. Schneider: Focus on Advances in Surface and Interface Science. New Journal of Physics 9 (2007).
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