Neural recommender system for the activity coefficient prediction andUNIFACmodel extension of ionicliquid‐solutesystems

For the ionic liquid (IL)‐solute systems of broad interest, a deep neural network based recommender system (RS) for predicting the infinite dilution activity coefficient ( γ ∞ ) is proposed and applied for a large extension of the UNIFAC model. In the RS, neural network entity embeddings are employed for mapping each IL and solute, and neural collaborative filtering is utilized to handle the nonlinearities of IL‐solute interactions. A...