A systematic comparison of hard- and soft-constrained physics-informed molecular machine learning with the Clapeyron equation

In molecular machine learning (ML), significant progress has been made on integrating fundamental thermodynamic relations into ML models. Such physics-informed approaches can be categorized as hard-constrained, where the thermodynamic relations are embedded in the model architecture, and soft-constr