The importance of energy and, in particular, transportation fuel to the global economy and standard of living on earth cannot be understated. With the ever-increasing population and the need for cleaner energy, the search for alternative fuel sources is an essential endeavor. Biofuels present one such alternative to traditional petroleum-based fuels. A significant challenge in screening the thousands of different biofuel candidates is the need for a detailed kinetic model of their combustion chemistry. The onus has traditionally been on the chemist to determine which reactions to include in a kinetic model. Developing a comprehensive list of relevant reactions based on chemical intuition is an arduous and time consuming process. Automating the process of generating reaction networks is an ongoing field of study. Reactive molecular dynamics (RMD) is one such automated approach for proposing reaction networks. Unlike most automated network generators, RMD is based on the underlying atomistic interactions and reactions are observed from atomic trajectories with femtosecond resolution. Although the atomic forces for RMD would ideally be computed with high level \textit{ab initio} methods or even density functional theory (DFT), the nano- to millisecond time scales that are required to observe combustion chemistry at moderate temperatures and pressures are much too long for DFT-RMD to be feasible. By contrast, the reactive force field (ReaxFF) renders classical RMD computationally tractable. By performing RMD simulations with ReaxFF, reaction pathways for various biofuels are identified without human intervention. Subsequently, transition state structures are located for the ReaxFF reactions and activation energies are computed at the DFT level of theory. The DFT calculations validate that the ReaxFF reaction pathways are physically realistic. The combined ReaxFF and DFT results provide molecular insight into the mechanisms that lead to soot formation and corroborate experimental data.

Elucidating biofuel sooting tendencies and mechanisms with reactive molecular dynamics and density functional theory

2019 Fall National Meeting

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