A database-based approach for predicting coupled cascade reaction kinetics in polymers: application to oxidative degradation kinetics of high-performance polymers |
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Authors: | Jayashrita Debnath Sooraj Kunnikuruvan Nishant Sinha Priya V. Parandekar Om Prakash Thomas K. Tsotsis |
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Affiliation: | 1. Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur, India.;2. Boeing Research &3. Technology, India-Center, Bangalore, India.;4. Technology, Huntington Beach, CA, USA. |
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Abstract: | Coupled cascade reactions forming complex reaction networks can be commonly found in polymerisation reactions and other reactions involving radical intermediates. Predicting the mechanism and kinetics of such reactions requires proper modelling of complex reaction networks. This becomes particularly difficult when coupled cascade reactions occur in polymeric systems containing different types of residues. Here, we propose a residue-based database approach to model such reactions in polymers, with the aid of a visual interface developed here. We demonstrate this approach by predicting the oxidative degradation kinetics of high-performance polymers (HPPs). First, we show that residue-based reaction database can be linked to construct the whole reaction network. For this purpose, we developed a database for oxidation reactions of commonly occurring residues in industrially important HPPs. Then we implement a visual interface which takes inputs from a user about residues in a polymer of interest and subsequently link appropriate databases to build reaction network. Finally, this program executes numerical integration of rate equations in the back-end. Application of this approach and the developed program is demonstrated by studying the oxidative degradation kinetics of three well-known HPPs- PMR-15, HFPE-30 and PMR-II, where the computations took less than a minute in a conventional desktop computer. |
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Keywords: | First principle-based microkinetics database visualisation interface coupled cascade reactions polymer degradation |
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