ABSTRACT

Andreas W Goetz of the University of California, San Diego and Dionisios G Vlachos of the University of Delaware are supported by an award from the Chemical Theory, Models and Computational Methods (CTMC) program and the Computational and Data-Enabled Science and Engineering (CDS&E) program in the Chemistry Division. The Division of Advanced Cyberinfrastructure (ACI) is co-funding this award. Goetz and Vlachos develop and apply computational tools for bifunctional catalysis. The project is an international collaboration with Philippe Sautet, Paul Fleurat-Lessard and Carine Michel of the Ecole Normale Superieure de Lyon in France who provide complimentary expertise and who are supported by a corresponding award of the French ANR. This project develops computational models and software capable of handling the multiscale nature and the complexity inherent to the catalytic processes entailing bifunctional catalysts in solution phase. Bifunctional catalysts are important for the conversion of biomass into liquid fuels and chemicals and therefore for a sustainable future that does not rely on dwindling petroleum sources and minimizes global warming with significant societal impact. Computer simulations can play a key role in understanding how these catalysts function and in guiding development of improved catalysts and industrially viable processes. The computational methods developed are integrated into freely available open source software libraries and distributed with a widely used molecular simulation package. Both graduate and undergraduate students are involved in the project, as well as high school students and teachers via internships and research experience programs to train the next generation of scientists. The work has relevance for multiple domains ranging from chemistry to chemical engineering to biosciences and aids the development of biorefineries with a clear impetus on economic growth and reduced CO2 emissions.


The developments in this project encompass a new force field and linear energy relations for fast screening of catalytic reaction networks, microkinetic simulations to extract the kinetically important steps, molecular dynamics simulations with quantum mechanics/molecular mechanics (QM/MM) algorithms that allow an adaptive exchange of particles across the QM/MM boundary to determine the activation energies of the important reactions, and parameterizations of density functional tight binding theory to maximize the accessible time scales. The combination of these methods enables for the first time to explore the combinatorial explosion in pathways in the transformation of biomass using bifunctional (a metal and an acid/base) catalysts in solution. Initially the project focuses on the hydrodeoxygenation of glycerol into propanediol, for which significant experimental data is available. These simulations aid in the development of improved bifunctional catalysts that can ultimately lead to improved processes in biorefineries. The integration of efficient multi-scale simulation approaches in widely utilized and freely available open source software as part of this project can impact multiple application domains.

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