Atomically precise phosphine-stabilized gold nanoclusters are commonly characterized by single-crystal X-ray diffraction, yet the extent to which these static structures represent finite-temperature behavior remains unclear. To explore the free-energy landscapes, equilibrium populations, and isomerization kinetics of t...
Caitlin A. McCandler, D. Sanwal, Jutta Rogal· 0 citations
This work develops a canonical parameterization, and trains energy-based generative flow networks to approximate the Boltzmann distribution over crystal structures for target molecules and space groups, and sample and analyze distributions of crystals for two molecules.
Michael Kilgour, A. Dong, M. Tuckerman et al.· 1 citation
JANUS is a multimodal neural sampler that couples continuous and masked discrete diffusion through an equivariant graph neural network trained directly from energy evaluations, without pre-generated equilibrium data, providing a foundation for thermodynamic sampling, characterization and inverse design of chemically di...
Denis Blessing, Mou-Yang Cheng, M. Schebek et al.· 2 citations
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