The solvation thermodynamics of rose acetate in four mixed solvents: Molecular dynamics simulation, molecular conformation analysis, machine learning and solubility prediction

Abstract

The solubility of rose acetate (alpha-(trichloromethyl) benzyl acetate) in four binary solvent mixtures was measured by static gravimetric method at the temperature ranging from 288.15 K to 328.15 K under atmosphere pressure. The dissolution behavior and solubility prediction were performed through simulations and calculations, using Materials Studio software and Back Propagation Neural Network. The modified Apelblat equation, λh model, Van’t Hoff equation, and NRTL model were employed to correlate the solubility data respectively. And the modified Apelblat equation provided the best fitting performance, corresponding to the lowest average value of average relative deviation and root mean square deviation. After analyzing the solvent properties, it was obsersved that the solubility of rose acetate in selected solvents was influenced by the polarity of the solvent. The mixing thermodynamic properties including ΔmixH, ΔmixS and ΔmixG indicated that the dissolution process of rose acetate was exothermic and spontaneous.Molecular dynamics (MD) simulations were utilized to analyze the interaction mechanism between rose acetate and binary solvent mixtures. The results revealed that the hydrogen bonding interaction played an insignificant role in the dissolution process. Moreover, the solute molecules were characterized in both crystal and solution state based on their conformation and molecular energies. A back-propagation (BP) neural network was constructed to predict the solubility of rose acetate, and the predicted data exhibited good agreement with the measured valuses.