Research
Hendrik Kraß works on machine learning for atomistic simulation and materials design, with a focus on metal-organic frameworks. His research evaluates learned interatomic potentials for predicting structural stability, material properties, and interactions with guest molecules. His publications also examine how generative models can support the design and synthesis of these porous materials.
Selected publications
- MOFSimBench: evaluating universal machine learning interatomic potentials in metal-organic framework molecular modeling 2026
- The Rise of Generative AI for Metal-Organic Framework Design and Synthesis 2025
Information reviewed 26 September 2026 · University profile