WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions
Rohan Yuri Sanspeur, Javier Heras-Domingo, John R. Kitchin, Zachary, Ulissi

TL;DR
WhereWulff is a semi-autonomous workflow that streamlines catalyst surface reactivity modeling by automating calculations, prioritizing surface terminations, and efficiently handling computational constraints, thus accelerating materials discovery.
Contribution
The paper presents a novel semi-autonomous workflow that reduces computational effort and automates complex tasks in catalyst surface modeling, enabling broader and more efficient exploration of materials.
Findings
Halved the number of DFT calculations needed.
Automated job resubmission under resource constraints.
Validated workflow on oxygen evolution reaction surfaces.
Abstract
This paper introduces WhereWulff, a semi-autonomous workflow for modeling the reactivity of catalyst surfaces. The workflow begins with a bulk optimization task that takes an initial bulk structure, and returns the optimized bulk geometry and magnetic state, including stability under reaction conditions. The stable bulk structure is the input to a surface chemistry task that enumerates surfaces up to a user-specified maximum Miller index, computes relaxed surface energies for those surfaces, and then prioritizes those for subsequent adsorption energy calculations based on their contribution to the Wulff construction shape. The workflow handles computational resource constraints such as limited wall-time as well as automated job submission and analysis. We illustrate the workflow for oxygen evolution (OER) intermediates on two double perovskites. WhereWulff nearly halved the number of…
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Taxonomy
TopicsMachine Learning in Materials Science · Catalytic Processes in Materials Science · Catalysis and Oxidation Reactions
