New graph-based computational methods for dealing with chemical reactivity and catalysis
DOI:
https://doi.org/10.2436/20.2003.01.142Keywords:
Reaction networks, computational chemistry, catalysis, cheminformaticsAbstract
The exponential growth of computing power has crystallized in a breakthrough in the predictive capability of theoretical and computational chemistry. In spite of this leap forward, the study of the reactivity of complex chemical systems, implying the treatment of very dense reaction networks, is still a challenge. In this article, we showcase three new methods that allow the generation, treatment and processing of catalytic cycles and complex reaction networks in an efficient automated manner. First, we present a tool for predicting the turnover frequency in catalytic cycles, both for homogeneous and heterogeneous catalysis. Then, we present what we have named the POMSimulator, a method for generating reaction maps and predicting speciation on the basis of pH and concentrations, as well as the formation mechanisms of complex molecular oxides. Lastly, we present OntoRXN, a new ontology for the formal definition of reaction mechanisms whose goal is to simplify the treatment and processing of complex chemical information of this type.
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