Accelerating research into bio-based FDCA-polyesters by using small scale parallel film reactors

Abstract

High Throughput experimentation has been well established as a tool in early stage catalyst development and catalyst and process scale-up today. One of the more challenging areas of catalytic research is polymer catalysis. The main difference with most non-polymer catalytic conversions is the fact that the product is not a well defined molecule and the catalytic performance cannot be easily expressed only in terms of catalyst activity and selectivity. In polymerization reactions, polymer chains are formed that can have various lengths (resulting in a molecular weight distribution rather than a defined molecular weight), that can have different compositions (when random or block co-polymers are produced), that can have cross-linking (often significantly affecting physical properties), that can have different endgroups (often affecting subsequent processing steps) and several other variations. In addition, for polyolefins, mass and heat transfer, oxygen and moisture sensitivity, stereoregularity and many other intrinsic features make relevant high throughput screening in this field an incredible challenge. For polycondensation reactions performed in the melt often the viscosity becomes already high at modest molecular weights, which greatly influences mass transfer of the condensation product (often water or methanol). When reactions become mass transfer limited, catalyst performance comparison is often no longer relevant. This however does not mean that relevant experiments for these application areas cannot be performed on small scale. Relevant catalyst screening experiments for polycondensation reactions can be performed in very efficient small scale parallel equipment. Both transesterification and polycondensation as well as post condensation through solid-stating in parallel equipment have been developed. Next to polymer synthesis, polymer characterization also needs to be accelerated without making concessions to quality in order to draw relevant conclusions.