Title

A surrogate model construction strategy for bio-oil using ReaxFF molecular dynamics

Conference Dates

June 16-21, 2019

Abstract

Surrogate fuel model is useful as representative of simplified complex fuel mixture in description of their chemical kinetics in pyrolysis or oxidation conditions. This work propose a surrogate model construction strategy for bio-oil using ReaxFF molecular dynamics. A 24-component bio-oil model was constructed as a baseline model for real bio-oil based on the literature reported data of GC-MS analysis for bio-oil yielded from fast pyrolysis of Pterocarpus Indicus. According to the chemical constituent and functional groups in the 24-component bio-oil model, 5 surrogate bio-oil models each containing 6 components were formulated. ReaxFF MD simulations are performed on the 6-component surrogates and the 24-component oil model under the same oxidation conditions. In addition to element ratio comparison, the surrogate models are validated by comparing the simulated temporal evolution of major reactants and products including radicals using the 24-component model as a baseline.

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