Computational Workflows
Computational workflows encode a multistep simulation procedure (structure generation, job submission, error handling, restarts and analysis) as a graph of tasks that a workflow engine such as FireWorks or AiiDA executes with little human supervision. They make high-throughput density functional theory practical and reproducible, record provenance, and can embed decision rules that choose which calculations to run next.
WhereWulff: an autonomous OER workflow for oxides (2023)
WhereWulff encodes the full oxygen evolution reaction modeling procedure for oxides in a FireWorks, pymatgen, atomate and Custodian stack, from bulk magnetic-ordering search and Pourbaix stability through slab enumeration, surface energies, Wulff-shape facet prioritization, surface Pourbaix termination selection and overpotential calculation (Sanspeur et al. 2023). Its decision steps cut the DFT count for two double perovskites from about 240 to about 132, and a ContinueOptimizeFW task with FireWorks detours handled about 180 wall-time resubmissions automatically while passing geometry, moments and wavefunctions between jobs. An end-to-end regression test on IrO2 with simulated VASP runs on every merge, and the same mechanism allows restarting a workflow mid-graph. Summary: sanspeur2023.