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cs.LG2026
Thermodynamically consistent machine learning model for excess Gibbs energy
Marco Hoffmann, Thomas Specht, Quirin Göttl +4
The excess Gibbs energy plays a central role in chemical engineering and chemistry, providing a basis for modeling thermodynamic properties of liquid mixtures. Predicting the exces…
cs.LG2025
GRAPPA -- A Hybrid Graph Neural Network for Predicting Pure Component Vapor Pressures
Marco Hoffmann, Hans Hasse, Fabian Jirasek
Although the pure component vapor pressure is one of the most important properties for designing chemical processes, no broadly applicable, sufficiently accurate, and open-source p…