Functional microgels with tailored structure and specific properties are required for medical and technical applications, thus motivating model-based optimization of their fabrication processes. An important step in the creation of accurate models is parameter estimation. We present a methodology for a parameter identifiability analysis, which approximates the feasible parameter set as a box by solving a series of constrained dynamic optimization problems. The method is applied to the synthesis of microgels based on two monomers, N-vinylcaprolactam and N-isopropylacrylamide, and the cross-linker N,N-methylenebis(acrylamide). The results show that kinetic parameters corresponding to the reaction of the monomers are identifiable as are a subset of the kinetic parameters involving the cross-linker. The reaction kinetics of the cross-linking are faster in comparison to the main polymerization reaction for N-vinylcaprolactam; this allows for an improved understanding of the occurring reaction phenomena. The reaction kinetics of the cross-linking are not identifiable for N-isopropylacrylamide for the given experimental setup; model-based experimental design for parameter precision might enable their identification. The results also indicate potential for model simplification and allow us to make suggestions toward the enhancement of Raman spectroscopy measurements.

Enzymes are nature’s catalysts and have great potential for sustainable processes from renewable resources. The adaptation of enzymes to the requirements of industrial processes is a prerequisite to harness their...

Modelling and synthesis go hand in hand to efficiently engineer copolymer microgels with various architectures: core–shell structures (with ferrocene mainly in the core or in the shell) and also microgels with homogeneous comonomer distribution.

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Microgels are functional polymer colloids with diverse applications, for example, in medicine, engineering, or agriculture. Some applications require large microgels in the size range of μm, which could previously only be synthesized using microfluidics or a synthesis procedure involving a fed-batch reaction with a temperature ramp. We use dynamic optimization to determine a simpler synthesis recipe that allows us to synthesize microgels in the μm range using a batch procedure. First, a sensitivity analysis shows that the microgel size is sensitive to the initial concentration of initiator and the reactor temperature. Second, the dynamic optimization yields a batch recipe that provides microgels of the desired μm size range. The recipe uses a low initial initiator concentration and a low reactor temperature. The respective recipe is validated experimentally; model simulation results and experimental measurements of the hydrodynamic diameter show good agreement.

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