MC16 2023 - Poster Book of abstracts

Computer-vision assisted colorimetric analysis of the UV-promoted degradation of polyurethane foams Timothy McCabe, Marc Reid Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, UK Kineticolor , a software developed by Reid Group Research at the University of Strathclyde, uses computer-vision to give reproducible, quantification of temporally- and spatially resolved colorimetric and kinetic information. Kineticolor has already been used in advancing the understanding of catalyst degradation kinetics 1 as well as providing a computer-vision enabled platform for the analysis of mixing phenomena in chemical and non-chemical processes. 2 Urethane containing polymers are known to be susceptible to degradation by UV radiation. This degradation can have a negative effect on the mechanical, physical and aesthetic properties of the material.This poster reports the use of the same computer-vision based system to enhance the colorimetric analysis of the photodegradation of polyurethane foams. ∆E , a measure of average contrast change calculated from the CIE- L*a*b* colour space, was extensively studied, and demonstrated time resolved changes across the top surface of different polyurethane foams. Kineticolor also provides a pixel-by-pixel visualisation of contrast change, resulting in a ∆E heat-map which demonstrates subtle changes in the polymer surface over time. FT-IR and TGA analyses are also reported alongside computer-vision derived colorimetric information. Use of thermogravimetric and spectroscopic information in conjunction with colorimetric data has been investigated todemonstrate chemical differences caused by photodegradation. FT-IR difference spectra were used to investigate subtle chemical changes in the foam as a result of UV degradation. References 1. Yan, M. Cowie, C. Howcutt, K. Wheelhouse, N. Hodnett, M. Kollie et al . Chem. Sci. , 2023, Advance Article DOI: 10.1039/ D2SC05702F 2. Barrington, A. Dickinson, J. McGuire, C. Yan, M. Reid, Org. Process Res. Dev ., 2022, 26 , 3073-3088 DOI: 10.1021/acs. oprd.2c00216

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