Fuzzy viscometric analysis of polymer–polymer miscibility based on fuzzy regression

• The Quadratic Programming estimates the viscometric parameters under fuzziness.
• The possibility theory allows the fuzzy prediction of polymer–polymer miscibility.
• The possibility/necessity degree enables a more flexible estimation of miscibility.

This study investigates the application of fuzzy regression to the viscometric analysis of polymer–polymer miscibility by using experimental viscosity data for polystyrene (PS), poly(styrene-co-acrylonitrile) (PSAN) and PS/PSAN blends in CHCI3 and DMF at different temperatures. The first stage includes the calculations of the fuzzy thermodynamic interaction parameter based on the results from the fuzzy regression models. In the second stage, the possibility and necessity measure-dependent results of the immiscibility (or miscibility) are presented and compared with the traditional miscibility estimations. This study shows that the fuzzification of traditional regression as well as the decision making on miscibility may have a good potential to be used for viscometric studies.