Automated descriptor selection, volcano curve generation, and active site determination using the DescMAP software

The material space for catalyst discovery is expansive. Volcano curves are traditionally employed to provide physical insights into optimal catalyst characteristics for new material selection. Their generation lies on a single descriptor picked using expert knowledge. Here we present DescMAP, a Python-based software, to automate the selection of descriptors, the generation of volcano maps, and the identification of active sites for structure-sensitive reactions. We consider traditional energy-based and geometric descriptors for structure-sensitive reactions. DescMAP is integrated with the Virtual Kinetic Laboratory (VLab) to provide multiple functionalities. It inputs spreadsheets or template files for flexibility and outputs interactive graphs for post-processing. We demonstrate its features using the non-oxidative dehydrogenation of ethane to ethylene over (111) closed-packed surfaces and the methane total oxidation over various Pt facets. It can be easily applied to other complex chemistries and achieves quick screening of potential catalysts. Program title: DescMAP CPC Library link to program files: https://doi.org/10.17632/g399b3xyfy.1 Developer's repository link: https://github.com/VlachosGroup/DescriptorMap Code Ocean Capsule: https://codeocean.com/capsule/7598436 Licensing provisions: MIT license Programming language: Python External routines: pMuTT, NumPy, Pandas, Matplotlib, Plotly, Scikit-learn, Scipy Nature of problem: Screening potential catalysts via microkinetic modeling and generating volcano curves is time-consuming. An automated tool to accelerate this process is lacking. Solution method: Python package with descriptor selection that automates descriptor-based microkinetic modeling. Interactive volcano curves generated for post-analysis.