Murphy, MadelineNoordhoek, KyleGathmann, SallyeDauenhauer, PaulBartel, Chris2024-12-022024-12-022024-12-02https://hdl.handle.net/11299/268118The `programmable-loop-directionality` zip includes any (individual) plots which appear in our manuscript related to data statistics, feature importance, and model performance. The folder also includes the data and scripts used to generate and analyze the machine learning models as well as the data and scripts used to set-up/run the microkinetic models and generate the microkinetic model results (pre-machine learning analysis) Each subfolder contains a detailed README.md file that provides additional information related to the data and scripts contained within.This repository exists to share the data and scripts used in the paper "Catalytic Resonance Theory: Forecasting the Flow of Programmable Catalytic Loops" by Madeline Murphy, Kyle Noordhoek, Sallye Gathmann, Paul Dauenhauer, and Christopher Bartel. The bulk of the files are contained within the `programmable-loop-directionality` folder with additional detailed information presented in the `README.md` files of each subfolder. Here we also include zips containing each of the Random Forest models that were trained along with the full grid searches generated during the study.Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Programmable CatalysisMachine LearningMicrokinetic ModelingDataset