ML model based on support vector regression integrating experimental data, COSMO-RS simulations, and cheminformatic descriptors for computing the melting points of deep eutectic solvents and predicting solid-liquid equilibriums

Melty Molecule is a molecular property prediction system that leverages graph neural networks to predict melting points of chemical compounds. The model uses a hybrid architecture combining Principal Neighborhood Aggregation (PNA) and Graph Isomorphism Networks (GIN) with edge updates and virtual node connectivity.

SMILES converted into Graphs that contains atomic information, bonding informatics. Graphs considered as input for the NN to Predict Melting Pont of Liquid Crystals (LCs)