COMPUTER AIDED MOLECULAR DESIGN OF SOLVENTS FOR DISTILLATION PROCESSES Braam van Dyk and Izak Nieuwoudt * Institute for Thermal Separation Technology, Department of Chemical Engineering, University of Stellenbosch, South Africa. ABSTRACT A Genetic Algorithm based CAMD model was extended to design improved solvents and solvent mixtures for extractive distillation, azeotropic distillation, liquid extraction and liquid chromatography. The algorithm was applied to a number of industrially relevant separation problems. In each case solvents were found that are predicted to perform substantially better than those that are currently used in industry. Keywords: Solvents, Distillation, CAMD INTRODUCTION Separation processes are an integral part of chemical engineering. The purity of a chemical product is among the principal factors influencing its value. Therefore, any method that can increase the purity of a product or decrease the cost of purification will have a direct effect on the profitability of the entire plant. An important class of separation processes is the solvent-based separations. This includes processes like extractive distillation, liquid-liquid extraction and chromatographic separation. Heterogeneous azeotropic distillation is closely related to these processes. The most important variable in the design of a solvent-based separation process is the choice of solvent. In the last two decades, several computer aided molecular design methods (CAMD) have seen the light[1-8]. The pros and cons of these methods have been reviewed by van Dyk[9]. A genetic algorithm for the computer-aided molecular design of solvents, called SolvGen, has been developed previously by the authors[10]. In this paper, improvements to the basic algorithm are presented. The algorithm was improved and expanded to include solvent mixtures, liquid-liquid extraction, heterogeneous