Monitoring of Photopolymerization Kinetics and Network Formation by Combined Ultrasonic Reflectometry and Near-infrared Spectroscopy

摘要

Using UV radiation, a polymer resin can be cured within seconds. Due to its advantages, this technique found many applications starting from adhesives, printing inks, exterior metal coatings, can coatings to automotive scratch resistant varnishes [1]. However, the understanding of the underlying processes during UV curing is not yet clear as it involves interactions of physical processes, like gelation and vitrification, and chemical reaction. Single analytical methods like real-time NIR spectroscopy, Photo-DSC, Raman spectroscopy etc. have been used to monitor the chemical reactions during UV curing [2-5]. But these methods do not allow simultaneous investigation of the relation between physical network formation and chemical conversion. An attempt was made by Khan et al. [6] to study chemical reaction and rheological properties of thiol-ene polymers using real-time FTIR and in situ Fourier transform mechanical spectroscopy. However, the two methods were not combined; conversion and moduli were not measured simultaneously. A method developed some years ago [7] by combining two ultrafast and in situ techniques such as ultrasonic (US) reflectometry and real-time near-infrared spectroscopy (RT-NIRS) was used in this study to achieve a better understanding of the UV curing kinetics and network formation of acrylates. Therefore, the curing of resins with varied reactive diluent concentration and photoinitiator concentration and at different exposure times was investigated. Simultaneous measurements of conversion and dynamic shear modulus have been used to study the transition from reaction controlled to diffusion controlled polymerization kinetics. Furthermore, the conversion-time curves, calculated from NIR measurements, were used to study the transition from light reaction kinetics to dark reaction kinetics. Finally, a model developed before [7] was used to describe the modulus-conversion curves.