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Accelerated discovery of multi-element CO2 electrocatalysts with human-in-the-loop

J. Kim, et al.

Contents of Repository

  • 01_DataAcquisition/ : Domain-knowledge guided next batch composition recommendation using Explainable Boosting Machine (EBM) with generalized additive models (GAMs).
  • 02_BayesOpt/ : Simulated Bayesian optimization experiments on a virtual composition–jpropylene space.
  • 03_Regression_XGB/ : Training and evaluation of XGBoost regression models using the complete experimental dataset for predicting electrocatalytic CO2 conversion to C3 hydrocarbons.
  • src/ : Utility functions and tools supporting the codes in this repository.

Data Availability

All the experimental data and the data used for model training are available on the Zenodo repository.

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