Johannes T. Margraf

Fritz Haber Institute of the Max Planck Society — Germany

Materials Science · Physical Sciences

46h-index7.0kcitations221works5.42yr avg
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Research Topics

Machine Learning in Materials Science(84), Advanced Chemical Physics Studies(41), Nuclear physics research studies(38), Computational Drug Discovery Methods(28), Atomic and Molecular Physics(21)

Publications220 total

Integrating Charge Equilibration with Equivariant Machine-Learning Interatomic Potentials
2026Open Access
Interplay between shape and composition in bimetallic nanoparticles revealed by an efficient optimal-exchange optimization algorithm
The Journal of Chemical Physics·2026Open Access
Spectral Tuning of Hyperbolic Shear Polaritons in Monoclinic Gallium Oxide via Isotopic Substitution
Advanced Materials·2026Open Access
CCDC 2414186: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
CCDC 2414188: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
CCDC 2414183: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
CCDC 2414187: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
CCDC 2414181: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
CCDC 2414185: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
CCDC 2414184: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
CCDC 2414182: Experimental Crystal Structure Determination
The Cambridge Structural Database·2025Open Access
Spectral tuning of hyperbolic shear polaritons in monoclinic gallium oxide via isotopic substitution - Data for figures
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
Spectral tuning of hyperbolic shear polaritons in monoclinic gallium oxide via isotopic substitution - Data for figures
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
A foundation model for atomistic materials chemistry
The Journal of Chemical Physics·2025· 65 citedOpen Access
Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery
Advanced Materials·2025· 1 citedOpen Access
Pushing charge equilibration-based machine learning potentials to their limits
npj Computational Materials·2025· 3 citedOpen Access
Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery
2025· 2 cited
Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials
Advanced Intelligent Discovery·2025· 1 citedOpen Access
Predict before You Precipitate: Learning Templating Effects in Hybrid Antimony and Bismuth Halides
Chemistry of Materials·2025Open Access
Pushing Charge Equilibration Based Machine Learning Potentials to their Limits
2025Open Access
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Frequent Co-authors

Karsten Reuter(17), Timothy Clark(14), U. Kneißl(14), H. H. Pitz(14), P. von Brentano(12), A. Zilges(12), Dirk M. Guldi(11), R.-D. Herzberg(10), R.D. Heil(8), C. Wesselborg(8), Volker Strauß(7), H. Friedrichs(7), I. Bauske(6), H. Maser(6), N. Pietralla(6), S. Lindenstruth(6), Gábor Cśanyi(5), Hyunwook Jung(4), Thomas Bein(3), Noam Bernstein(3)