News

Date	News
23.10.2025	New Paper on Learning Crystallographic Disorder
16.09.2025	Exploring the Limits of Machine Learned Charge Equilibration
16.09.2025	Designing Molecular Photoswitches with Generative Machine Learning
09.07.2025	Stress Testing Atomistic Foundation Models
12.06.2025	Work on Self-assembly of Cyclic Nanoarchitectures in ACS Nano
02.06.2025	Predicting Templating Effects in Solid-Synthesis with Machine Learning
24.04.2025	Efficient Higher-Order Derivatives for Machine Learning Potentials
27.03.2025	New Multi-Fidelity Machine Learning Paper by Mengnan
20.02.2025	Testing Alternative Dispersion Corrections for a Bayesian Functional
12.12.2024	New paper on machine learning for vibrational spectra
26.11.2024	Workshop on Machine Learning for Molecules
15.08.2024	Efficient density functional approach in J. Chem. Phys.
29.07.2024	Insights on metal dusting resistance in new paper
12.07.2024	Mengnan reports comprehensive DFTB parameter set
30.04.2024	European Collaboration on Growth Kinetics of Graphene
24.04.2024	New Paper on Molecular Graph Embedding
24.03.2024	New paper on high-entropy alloys in JACS
23.11.2023	New Preprint on Multiobjective Machine Learning for Catalyst Design
16.11.2023	New Paper on Estimating Free Energy Barriers with Machine Learning
09.11.2023	Going live at Uni Bayreuth

Faculty of Biology, Chemistry & Earth Sciences