EASIQ-Marcus: An Automated Workflow for Applying Marcus Theory to Computational Chemistry Output Files

Single-electron transfer (SET) and energy-transfer (EnT) events play a central role in contemporary mechanistic proposals across photochemistry, electrochemistry, and catalysis. However, in routine computational practice, these steps are often treated less systematically than conventional bond-forming or bond-breaking events because their barrier evaluation usually requires a Marcus-theory workflow built from multiple quantum-chemical calculations, solvent-state manipulations, and careful post-processing of energies. Here, we present EASIQ-Marcus (https://github.com/maserasgroup-repo/easiq_marcus/), a Python package that automates this practical workflow for Gaussian users. The code implements several literature approaches for estimating reorganization energies and barriers, including hard-sphere, simplified hard-sphere, and four-point Marcus strategies in both symmetric and asymmetric forms. By turning the required file preparation and data extraction into explicit command-line steps, EASIQ-Marcus is designed to make the practical evaluation of SET and EnT events transparent, reproducible, and suitable for routine mechanistic studies.