ReNeGate: A Reaction Network Graph-Theoretical Tool for Automated Mechanistic Studies in Computational Homogeneous Catalysis

Exploration of the
chemical reaction space of chemical
transformations
in multicomponent mixtures is one of the main challenges in contemporary
computational chemistry. To remove expert bias from mechanistic studies
and to discover new chemistries, an automated graph-theoretical methodology
is proposed, which puts forward a network formalism of homogeneous
catalysis reactions and utilizes a network analysis tool for mechanistic
studies. The method can be used for analyzing trajectories with single
and multiple catalytic species and can provide unique conformers of
catalysts including multinuclear catalyst clusters along with other
catalytic mixture components. The presented three-step approach has
the integrated ability to handle multicomponent catalytic systems
of arbitrary complexity (mixtures of reactants, catalyst precursors,
ligands, additives, and solvents). It is not limited to predefined
chemical rules, does not require prealignment of reaction mixture
components consistent with a reaction coordinate, and is not agnostic
to the chemical nature of transformations. Conformer exploration,
reactive event identification, and reaction network analysis are the
main steps taken for identifying the pathways in catalytic systems
given the starting precatalytic reaction mixture as the input. Such
a methodology allows us to efficiently explore catalytic systems in
realistic conditions for either previously observed or completely
unknown reactive events in the context of a network representing different
intermediates. Our workflow for the catalytic reaction space exploration
exclusively focuses on the identification of thermodynamically feasible
conversion channels, representative of the (secondary) catalyst deactivation
or inhibition paths, which are usually most difficult to anticipate
based solely on expert chemical knowledge. Thus, the expert bias is
sought to be removed at all steps, and the chemical intuition is limited
to the choice of the thermodynamic constraint imposed by the applicable
experimental conditions in terms of threshold energy values for allowed
transformations. The capabilities of the proposed methodology have
been tested by exploring the reactivity of Mn complexes relevant for
catalytic hydrogenation chemistry to verify previously postulated
activation mechanisms and unravel unexpected reaction channels relevant
to rare deactivation events.