In-depth analysis of reaction kinetics parameters of phenolic resin using molecular dynamics and unsupervised machine learning approach

AS Bhesania and P Kamboj and SA Peddakotla and R Kumar, COMPUTATIONAL MATERIALS SCIENCE, 206, 111215 (2022).

DOI: 10.1016/j.commatsci.2022.111215

Reaction kinetics parameters of a material depend on energy dynamics based on breaking and formation of all the types of bonds in the system. While employing molecular dynamics simulation, it can become tedious and a complicated job to use all the bond information for extracting reaction kinetics parameters. With this understanding, in the current study, the use of an unsupervised machine learning technique is demonstrated for extracting the reaction kinetics parameters from the molecular dynamics simulation of an ablative material. Molecular dynamics simulations are performed on crosslinked and non-crosslinked polymers in temperature regime where they would undergo pyrolysis decomposition. Non-negative Matrix Factorization (NMF) technique is used to reduce the bonding environment, obtained during the simulations, to the concentration profiles of a few principal components. A comparative analysis performed with polymers having different degrees of crosslinking reveals that the activation energy reduces with increase in the degree of crosslinking. The effect of heating rate on the reaction kinetics of phenolic polymers during the pyrolysis simulation is investigated in detail. The assumption of chemical equilibrium between gases and porous solid domain is frequently made in continuum level thermal response solvers. It is unknown if this assumption significantly affects the calculated reaction kinetics parameters. To understand the same, a molecular dynamics simulation, which eliminates the generated gas molecules in a systematic manner throughout the pyrolysis process, is carried out. Furthermore, to demonstrate the usefulness of reaction kinetics parameters extracted after manifestation of chemical equilibrium at microscale level, a one-dimensional heat conduction analysis is performed. The results obtained by not considering the gas particles in reaction modeling agree well with experiments. At the end, a multiscale thermal response analysis is performed over an axi- symmetric geometry for which, a relation is derived between pyrolysis gas species and solid material density evolution from MD simulations. Based on the relation, the axi-symmetric domain is segregated into different regions for their contribution in changing pyrolysis gas composition by either adding or consuming gas species.

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