Calculating Hansen Solubility Parameters of Polymers with Genetic Algorithms

In materials engineering, it is often essential to know what are the best solvents to process any polymer, and employing methods based on Hansen solubility parameters are an effective way to find them. In this work the Hansen solubility parameters of polyether sulfone, lignin, and bitumen have been calculated by an alternative optimization procedure. It has been shown that, by applying an evolutionary strategy to Hansen's correlation method, it is possible to improve the fitting of solubility spheres. Compared with previous calculations, most quality-of-fit parameters are optimized. As a result, the sphere radii are reduced and, except for lignin, at least one of the solubility parameters is considerably changed (by 0.9-1.5 MPa1/2). Shortcomings of the correlation method are also pointed out, such as lack of data quality evaluation on set of solvents and uncertain character for partially solving solvents. At least the former could be handled by a proposed parameter called fill factor. (C) 2013 Wiley Periodicals, Inc.