48 citations · 56 across the 8 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
physics.chem-ph2026
Composition-Dependent Self-Diffusion Coefficients in Liquid Mixtures from Hybrid Machine Learning
Jens Wagner, Thomas Specht, Hans Hasse +1
Self-diffusion coefficients are key descriptors of molecular mobility, yet experimental data remain scarce, highlighting the need for reliable prediction methods. In previous work,…
physics.chem-ph2026
Hybrid Machine Learning for Enhanced Prediction of Diffusion Coefficients in Liquids
Jens Wagner, Zeno Romero, Kerstin Münnemann +4
Diffusion coefficients are key thermophysical properties for modeling mass transport in liquids, but experimental data are scarce, making reliable prediction methods indispensable.…