Enzymatic Polycondensation of 1,6-Hexanediol and Diethyl Adipate: A Statistical Approach Predicting the Key-Parameters in Solution and in Bulk

• Published in: Polymers
• Main Authors: Nasr, Kifah, Meimoun, Julie, Favrelle-Huret, Audrey, Winter, Julien De, Raquez, Jean-Marie, Zinck, Philippe
• Format: Text
• Language: English
• Published: MDPI 2020
• Subjects: Article; Antarc*; Antarctica
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565462/; http://www.ncbi.nlm.nih.gov/pubmed/32847050; https://doi.org/10.3390/polym12091907

Among the various catalysts that can be used for polycondensation reactions, enzymes have been gaining interest for three decades, offering a green and eco-friendly platform towards the sustainable design of renewable polyesters. However, limitations imposed by their delicate nature, render them less addressed. As a case study, we compare herein bulk and solution polycondensation of 1,6-hexanediol and diethyl adipate catalyzed by an immobilized lipase from Candida antarctica. The influence of various parameters including time, temperature, enzyme loading, and vacuum was assessed in the frame of a two-step polymerization with the help of response surface methodology, a statistical technique that investigates relations between input and output variables. Results in solution (diphenyl ether) and bulk conditions showed that a two-hour reaction time was enough to allow adequate oligomer growth for the first step conducted under atmospheric pressure at 100 °C. The number-average molecular weight (M(n)) achieved varied between 5000 and 12,000 g·mol(−1) after a 24 h reaction and up to 18,500 g∙mol(−1) after 48 h. The statistical analysis showed that vacuum was the most influential factor affecting the M(n) in diphenyl ether. In sharp contrast, enzyme loading was found to be the most influential parameter in bulk conditions. Recyclability in bulk conditions showed a constant M(n) of the polyester over three cycles, while a 17% decrease was noticed in solution. The following work finally introduced a statistical approach that can adequately predict the M(n) of poly(hexylene adipate) based on the choice of parameter levels, providing a handy tool in the synthesis of polyesters where the control of molecular weight is of importance.