FHI Theory

Theory Department

The research in the Theory Department focuses on a quantitative modeling of materials properties and functions, and in particular on processes in working catalysts and energy conversion devices. For this we advance and employ predictive-quality multiscale models, advanced data science techniques and machine learning, thereby straddling the frontiers of physics, chemistry, computing sciences, as well as materials science and engineering.


Recent publications

 

Out of the Crystalline Comfort Zone: Sampling the Initial Oxide Formation At Cu(111)

Out of the Crystalline Comfort Zone: Sampling the Initial Oxide Formation At Cu(111)


F. Riccius, N. Bergmann, H.H. Heenen, K. Reuter 
Adv. Sci. e13878 (2025)

Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery

Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery


K.S. Jakob, A. Walsh, K. Reuter, J.T. Margraf
Adv. Mater. e14226 (2025)

Machine Learning the Energetics of Electrified Solid-Liquid Interfaces

Machine Learning the Energetics of Electrified Solid-Liquid Interfaces


N. Bergmann, N. Bonnet, N. Marzari, K. Reuter, N.G. Hörmann
Phys. Rev. Lett. 135, 146201 (2025)

Pushing charge equilibration-based machine learning potentials to their limits

Pushing charge equilibration-based machine learning potentials to their limits


M. Vondrák, K. Reuter, J.T. Margraf
npj Computational Materials 11, 288 (2025)

Spin-informed universal graph neural networks for simulating magnetic ordering

Spin-informed universal graph neural networks for simulating magnetic ordering


W. Xu et al.
PNAS 122, e2422973122 (2025)

Electron Spillover into Water Layers: A Quantum Leap in Understanding Capacitance Behavior

Electron Spillover into Water Layers: A Quantum Leap in Understanding Capacitance Behavior


L. Li, T. Eggert,  K. Reuter, N.G. Hörmann
JACS 147, 22778 (2025)
 

Origin of Electrocatalytic Selectivity during the Oxygen Reduction Reaction on Au(111)

Origin of Electrocatalytic Selectivity during the Oxygen Reduction Reaction on Au(111)


E. Diesen, A.M. Dudzinski, K. Reuter, V.J. Bukas
ACS Catalysis 15, 5403 (2025)

Automatic Process Exploration through Machine Learning Assisted Transition State Searches

Automatic Process Exploration through Machine Learning Assisted Transition State Searches


K.C. Lai, P. Poths, S. Matera, C. Scheurer, K. Reuter
Physical Review Letters 134, 096201 (2025)

Theory Department News

Manipulating Light at the Nanoscale

Manipulating Light at the Nanoscale

January 14, 2026

A large international collaboration of researchers led by the Fritz Haber Institute, the Paul Drude Institute, and the University of Iowa proposes a new way to control how light moves through materials at extremely small scales. This approach could lead to better sensors, faster communications, and smaller optical devices.  more

Dr. Poths jump-starts her independent junior group in the Theory Department, supported by a prestigious Liebig Fellowship

Dr. Poths jump-starts her independent junior group in the Theory Department, supported by a prestigious Liebig Fellowship

January 07, 2026

The Fritz Haber Institute is happy to announce that Dr. Patricia Poths has secured a prestigious Liebig Fellowship from the Fonds der Chemischen Industrie (FCI) to jump-start her independent junior group “Realistic Modeling of Catalyst Dynamics at Interfaces”, within the Theory Department. 
  more

New International Study Uncovers Major Limitations in AI-Driven Materials Discovery 

New International Study Uncovers Major Limitations in AI-Driven Materials Discovery 

December 11, 2025

A new study led by the University of Bayreuth and our Institute´s Theory Department reveals that widely used computer simulations and artificial intelligence tools often make significant errors when predicting the properties of next-generation, high-performance materials. Published in the prestigious journal Advanced Materials, the research identifies the root of these inaccuracies and introduces new methods to overcome them. more

Magnets for a Cleaner Future: ERC Synergy Grant Funds MAGNESIS to Unlock Magnetically Enhanced Catalysis

Magnets for a Cleaner Future: ERC Synergy Grant Funds MAGNESIS to Unlock Magnetically Enhanced Catalysis

November 06, 2025

Prof. Karsten Reuter, Director of the Theory Department at the Fritz Haber Institute of the Max Planck Society and a leading catalysis expert, has been awarded one of the 66 prestigious ERC Synergy Grants for “MAGNESIS—Magnetically Enhanced Electrocatalysis,” together with Prof. Galán-Mascarós (ICIQ, Spain), Prof. Jeppe V. Lauritsen (Aarhus University, Denmark), and Prof. David Écija (IMDEA Nanoscience, Spain). Over the next six years, the €12 million project will uncover how magnetic fields can help to drive electrochemical reactions more efficiently—from studying what happens at the atomic level to testing complete devices such as fuel cells and electrolyzers. more

When Code Meets Quantum: how Students from the Berliner Hochschule für Technik Helped Redesign a Research Tool

When Code Meets Quantum: how Students from the Berliner Hochschule für Technik Helped Redesign a Research Tool

August 15, 2025

What happens when you pair sharp programming minds with complex quantum chemistry challenges? At the Fritz Haber Institute (FHI), that mix just produced something exciting: an interactive visualization platform that helps scientists see and manage how they improve simulations of electronic properties of materials. more

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