Deep Reaction Network Exploration at a Heterogeneous Catalytic Interface

Characterizing the reaction energies and reaction barriers of complex reaction networks is central to catalyst development and optimization. Nevertheless, heterogeneous catalytic surfaces pose several unique challenges to automatic reaction network characterization, including large system sizes and open-ended reactant lists, that make ad hoc network construction and characterization the current state-of-the-art. Here we show how automated algorithms for exploring and characterizing reaction networks can be adapted to the constraints of heterogeneous systems using ethylene oligomerization on silica-supported single site Ga3+ catalysts as a model system. Using only graph-based rules for exploring the network and elementary constraints based on activation energy and system size for identifying network terminations, a comprehensive reaction network was generated for this system and validated against standard methods. The automated algorithm (re)discovers the classic Cossee-Arlman mechanism for this system that is hypothesized to drive major product formation while remarkably also predicting several new pathways for producing alkanes and coke precursors. This demonstration represents the largest heterogeneous catalyst (more than 50 atoms, with an open-ended pool of reactants) to be characterized using a quantum chemistry-based automated reaction method.