Published September 6, 2023 | Version v1
Software Open

Processing Scripts for Swiss Cat+ East A1 project related to the automated and high-throughput Bayesian Optimization of CO2 hydrogenation heterogeneous catalysts


Jupyter notebooks to process the raw data of DOI: 10.5281/zenodo.8314734.

  • Raw data are processed through the Jupyter Notebook A1_DataProcess.ipynb to perform calculations on the raw data from individual fixed bed testing results (A1_GX_FBData_XR16x_mean.csv, A1_GX_FBData_XDB4x_mean.csv, A1_GX_FBData_XDC4x_mean.csv, A1_GX_FBData_AllUnits_mean.csv, A1_GX_FBData_XR16x_std.csv, A1_GX_FBData_XDB4x_std.csv, A1_GX_FBData_XDC4x_std.csv, A1_GX_FBData_AllUnits_std.csv) per generation. For each generation, the processed catalytic data are merged with the synthesis and solid dispense data and further calculations are performed to generate the A1_GX_AllDataProcessed.csv file.
  • The aggregated data (A1_GX_AllData_Processed) from each generation (1, 2, 3, 4, 5 and 2NC) are merged through the Jupyter Notebook A1_MergeAllGeneration.ipynb to generate a fully aggregated file with all generations (AllGen_Merged.csv) and a condensed file for a given reaction temperature AllGen_275CDataProcessed_Merged.csv.



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