10 citations · 11 across the 9 of their papers we have counts for
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Markov State Models for Tracking Reaction Dynamics on Catalytic Nanoparticles
Caitlin A. McCandler, Chatipat Lorpaiboon, Timothy C. Berkelbach +1
Markov state models (MSMs) are a powerful tool to analyze and coarse-grain complex dynamical data into interpretable kinetic processes. This capability is particularly important in…
Assessing generative modeling approaches for free energy estimates in condensed matter
Maximilian Schebek, Jiajun He, Emil Hoffmann +3
The accurate estimation of free energy differences between two states is a long-standing challenge in molecular simulations. Traditional approaches generally rely on sampling multi…
Estimating Solvation Free Energies with Boltzmann Generators
Maximilian Schebek, Nikolas M. Froböse, Bettina G. Keller +1
Accurate calculations of solvation free energies remain a central challenge in molecular simulations, often requiring extensive sampling and numerous alchemical intermediates to en…
Scalable Boltzmann Generators for equilibrium sampling of large-scale materials
Maximilian Schebek, Frank Noé, Jutta Rogal
The use of generative models to sample equilibrium distributions of many-body systems, as first demonstrated by Boltzmann Generators, has attracted substantial interest due to thei…
Efficient mapping of phase diagrams with conditional Boltzmann Generators
Maximilian Schebek, Michele Invernizzi, Frank Noé +1
The accurate prediction of phase diagrams is of central importance for both the fundamental understanding of materials as well as for technological applications in material science…