Publications of Matthias Scheffler

Thesis - Diploma (1)

2006
Thesis - Diploma
Cao, Jie: Polymerization of Carbon Nitride - experimental and theoretical investigation.

Thesis - Master (5)

2022
Thesis - Master
Zhao, Bo: Identifying descriptors for the in-silico, high-throughput discovery of the thermal insulators for thermoelectric applications.
2021
Thesis - Master
Lim, Bruce: Discussion, implementation and demonstration of AI-guided active workflows.
Thesis - Master
Oehlers, Melina: Identifying exceptional data points in materials science using machine learning.
2016
Thesis - Master
Ahmetcik, Emre: Machine Learning of the Stability of Octet Binaries.
Thesis - Master
Kowalski, Hagen-Henrik: First-principles Study of Thermoelectric Magnesium Silicides with High-Throughput Techniques.

Thesis - Bachelor (1)

2018
Thesis - Bachelor
Müller, Paul Manuel: Thermal Conductivities of Group IV and Group III-V Compound Semiconductors from First Principles.

Working Paper (13)

2024
Working Paper
Bellini, Giulia, Frank Girgsdies, Gregor Koch, Spencer Carey, Olaf Timpe, Gudrun Auffermann, Matthias Scheffler, Robert Schlögl, Lucas Foppa and Annette Trunschke: CO Oxidation Catalyzed by Perovskites: The Role of Crystallographic Distortions Highlighted by Systematic Experiments and AI.
Working Paper
Foppa, Lucas and Matthias Scheffler: Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups.
Working Paper
Kokott, Sebastian, Florian Merz, Yi Yao, Christian Carbogno, Mariana Rossi, Ville Havu, Markus Rampp, Matthias Scheffler and Volker Blum: Efficient All-electron Hybrid Density Functionals for Atomistic Simulations Beyond 10,000 Atoms.
2023
Working Paper
Boley, Mario, Felix Luong, Simon Teshuva, Daniel F. Schmidt, Lucas Foppa and Matthias Scheffler: From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery.
Working Paper
Foppa, Lucas and Matthias Scheffler: Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance.
Working Paper
Lu, Shuaihua, Luca M. Ghiringhelli, Christian Carbogno, Jinlan Wang and Matthias Scheffler: On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials.
Working Paper
Speckhard, Daniel, Christian Carbogno, Luca M. Ghiringhelli, Sven Lubeck, Matthias Scheffler and Claudia Draxl: Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models.
2021
Working Paper
Boley, Mario and Matthias Scheffler: Learning Rules for Materials Properties and Functions.
2019
Working Paper
Kloppenburg, Jan, Lydia Nemec, Björn Lange, Matthias Scheffler and Volker Blum: The (3×3)-SiC-(¯1¯1¯1) Reconstruction: Atomic Structure of the Graphene Precursor Surface from a Large-Scale First-Principles Structure Search.
Working Paper
Mazheika, Aliaksei, Yanggang Wang, Rosendo Valero, Luca M. Ghiringhelli, Francesc Vines, Francesc Illas, Sergey V. Levchenko and Matthias Scheffler: Ab initio data-analytics study of carbon-dioxide activation on semiconductor oxide surfaces.
2018
Working Paper
Acosta, Carlos Mera, Runhai Ouyang, Adalberto Fazzio, Matthias Scheffler, Luca M. Ghiringhelli and Christian Carbogno: Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing.
2016
Working Paper
Ghiringhelli, Luca M., Christian Carbogno, Sergey V. Levchenko, Fawzi Roberto Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira and Matthias Scheffler: Towards a Common Format for Computational Materials Science Data.
Working Paper
Nieminen, R.M., S. Bonella, L. Drury, Matthias Scheffler and E. Molinari: Three European Centers of Excellence in Computational Science.
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