HiREX: High-Throughput Reactivity Exploration for Extended Databases of Transition-Metal Catalysts

A method is introduced
for the automated analysis of reactivity
exploration for extended in silico databases of transition-metal catalysts.
The proposed workflow is designed to tackle two key challenges for
bias-free mechanistic explorations on large databases of catalysts:
(1) automated exploration of the chemical space around each catalyst
with unique structural and chemical features and (2) automated analysis
of the resulting large chemical data sets. To address these challenges,
we have extended the application of our previously developed ReNeGate
method for bias-free reactivity exploration and implemented an automated
analysis procedure to identify the classes of reactivity patterns
within specific catalyst groups. Our procedure applied to an extended
series of representative Mn(I) pincer complexes revealed correlations
between structural and reactive features, pointing to new channels
for catalyst transformation under the reaction conditions. Such an
automated high-throughput virtual screening of systematically generated
hypothetical catalyst data sets opens new opportunities for the design
of high-performance catalysts as well as an accelerated method for
expert bias-free high-throughput in silico reactivity exploration.