Multi-Objective Molecular Design for Cooling Crystallisation Solvent

In this paper, a multi-objective optimisation method based on the Non-dominated sorting genetic algorithm II (NSGA-II) is proposed, which proves to be effective in solving the computer-aided molecular design (CAMD) problem in the design of solvents for cooling crystallisation. A multi-objective optimisation model has been developed for the CAMD problem of solvents in the crystallisation process with the toxicity, solubility parameters, and potential recovery of the solvents as objective functions and the feasibility of the molecular structure as constraints. The properties involved are to be calculated by the group contribution method, and the solubility parameters of the solute in the solvent are calculated based on the Universal Quasichemical Functional-group Activity Coefficients (UNIFAC) model. Based on this method, cooling crystallisation solvents for 2-mercaptobenzothiazole (MBT) and sebacic acid were designed. The results indicate that the proposed multi-objective CAMD framework exhibits a certain degree of generality. Even when the optimisation parameters and methods differ from those of other existing frameworks, it does not overlook the optimal solutions under specific design conditions. Furthermore, clustering of the Pareto front for MBT revealed that, since multi-objective optimisation does not aim to obtain a single optimal solution, it can identify multiple candidate solvents that balance potential yield and toxicity. This approach avoids the issue of single-objective optimisation, which tends to overemphasise potential yield at the expense of toxicity.