Automated Reaction Network Enumeration and Profiling Platform for Mechanism-Guided Catalyst Design and Reactivity Optimization.
TL;DR
RxnEnumProfiler is presented, a highly automated, GUI-enabled software platform for mechanism-guided molecular catalyst design and reactivity optimization that integrates quantum mechanical methods, semiempirical tight-binding approaches, and reactive machine-learning interatomic potentials into a unified end-to-end workflow for simultaneous multimetric catalyst scoring and parallel exploration of competing reaction pathways.
Abstract
The optimization of chemical reactions, both catalytic and noncatalytic, to simultaneously achieve high selectivity, activity, and stability remains a central challenge in homogeneous catalysis and synthetic organic chemistry. Traditional discovery pipelines rely heavily on labor-intensive experimental screening, while current automated computational workflows are often limited by incomplete end-to-end automation, restricted accessibility beyond expert computational chemists, integration of quantum-mechanical surrogate methods, and reliance on single or approximate performance descriptors. A general-purpose, turnkey software platform that extends accessibility beyond command-line execution and removes the need for programming expertise can empower nonexpert scientists to design molecular catalysts and optimize chemical reactions. Here, we present RxnEnumProfiler, a highly automated, GUI-enabled software platform for mechanism-guided molecular catalyst design and reactivity optimization that integrates quantum mechanical methods, semiempirical tight-binding approaches, and reactive machine-learning interatomic potentials into a unified end-to-end workflow for simultaneous multimetric catalyst scoring and parallel exploration of competing reaction pathways. This platform enables rapid, high-throughput evaluation of arbitrary objective performance descriptors and subsequent ranking of candidate compounds via reaction network enumeration and profiling, substantially expanding the accessible chemical design space and accelerating the discovery of high-performing molecular catalysts and reactions. The generality of this approach is demonstrated across three representative homogeneous catalytic systems─organocatalyzed asymmetric hydrogenation, Pd-catalyzed C-O cross-coupling, and ansa-metallocene-catalyzed isotactic propylene polymerization─as well as a noncatalytic transformation relevant to epoxy curing chemistry.