Monitoring the continuous manufacture of a polymeric foam via a thermokinetic-informed acoustic technique

Polymer foams are difficult to characterise due to rapidly evolving physical features from liquid to porous solid. Swift changes in volume, porosity and moduli render many techniques challenging for the characterisation of the foam curing during a manufacturing process. A technique that employs the longitudinal speed of sound of an ultrasonic signal, informed by a thermokinetic model, is proposed as an in situ, in-line, non-destructive and continuous monitoring tool during the production of rigid polyurethane foams. This study demonstrates that speed of sound measurements are suitable for (a) continuous characterisation of different foaming stages in the polymer reaction and curing; (b) determining the degree of cure for the continuous monitoring of foams, and (c) predicting mechanical properties (i.e., stiffness and Poisson's ratio) of cured foam samples. The validity of this monitoring technique is confirmed by comparison with well-established methods that use physical characteristics (e.g., expansion rate, electrical properties), thermo-kinetic models and mechanical testing. This method positions itself as a monitoring tool and convenient method for determining material stiffness during production.

STOCHASTIC MODELING OF LIVING/CONTROLLED COPOLYMERIZATIONS IN TUBULAR REACTORS WITH LATERAL FEED

It is known the controlled microstructure polymers production increase in continuous reactors due to all industrial advantages that this type of operation presents. In this paper, the synthesis via Nitroxide-Mediated Polymerization (NMP) of copolymers based on styrene and methyl methacrylate accomplished in a tubular reactor with lateral feed is modeled by Kinect Monte Carlo (kMC). This reactional configuration aims the copolymers production with originals microstructure and applications. There were obtained all the microstructural properties distributions of the synthesized material at interest and the conversion values, Polydispersity Index (PDI) and chains average molar mass are compared to experimental data. The conversion presented minimum and maximum deviation in the module of 0.61 and -21.85%, respectively. For the PDI and the molar mass, there were obtained minimum and maximum errors of 0.72%, 1.50%, -23.10% and 1.77%, respectively. It was verified that the formed product differed from the expected one in experiments. There were found copolymers of polystyrene-b-poly(methyl styrene-rand-methacrylate), not being found any region that presented composition gradient through the chains, differently than it had been foreseen in the experimental synthesis, results that show the relevance of a stochastic simulation in the process to make decisions in the context of polymer reaction engineering.