Computational Modeling for Biomass Pyrolysis Applications

Dellon, Lauren

doi:https://doi.org/10.21985/n2-b5yg-y684

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Computational Modeling for Biomass Pyrolysis Applications

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Biomass has the potential to be our country’s leading renewable source of energy. Specifically, fast pyrolysis is a promising method for the conversion of biomass to valuable fuels and chemicals. Given that fast pyrolysis has a residence time of about two seconds, computational methods are particularly useful in obtaining product distributions and characterizing important reaction pathways. This dissertation presents the development and application of multiple computational methods used to investigate two major roadblocks in the production of acceptable fuel sources. The first part of this work was the enhancement of a structure generation algorithm for producing libraries of representative structures of lignin for any biomass source. The added complexity allowed for the investigation of areas of feasible lignin space, that which includes all possible structures satisfying the experimental characteristics of monomer distribution, bond distribution, molecular weight distribution, and branching coefficient simultaneously. Additionally, these lignin libraries can subsequently be used in kinetic modeling studies and molecular simulations. The second part of this work was the development of a detailed microkinetic model for the zeolitic upgrading of biomass pyrolysis vapors. An automated network generator was used to construct a reaction network, and kinetic and thermodynamic parameters were estimated from group additivity, transition state theory, and density-functional theory. The framework established can serve as a platform to investigate different model compounds, zeolites, and operating conditions.

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