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20242026
most citedThermodynamically consistent machine learning model for excess Gibbs energy

2 citations · 2 across the 3 of their papers we have counts for

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cs.CE2025

MLPROP -- an open interactive web interface for thermophysical property prediction with machine learning

Marco Hoffmann, Thomas Specht, Nicolas Hayer +2

Machine learning (ML) enables the development of powerful methods for predicting thermophysical properties with unprecedented scope and accuracy. However, technical barriers like c…