Research data supporting "Multi-Variable Multi-Metric Optimization of Self-Assembled Photocatalytic CO2 Reduction Performance using Machine Learning Algorithms"
Repository URI
Repository DOI
Change log
Authors
Bonke, Shannon
Trezza, Giovanni
Bergamasco, Luca
Song, Hongwei
Description
Zip archive containing (i) tabulated photocatalytic test results from heuristic and learning algorithm guided optimization alongside the corresponding chromatograms (instrument output files .gcd and ASCII text export thereof); transient absorption spectra and data fits (ASCII txt); infrared spectra from isotopic labelling experiment (instrument .spa and ASCII text); and machine learning output including training/test sets, raw data for plots, SHAP values and data correlation plot sets (.xlsx and ASCII text).
Version
Software / Usage instructions
Text reader, Excel, Shimadzu LabSolutions CS, Thermo Fisher OMNIC (note data provided in raw and ASCII text formats)
Keywords
CO2 Reduction, Machine Learning, Micelles, Photocatalysis
Publisher
Sponsorship
European Commission Horizon 2020 (H2020) Future and Emerging Technologies (FET) (828838)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (891338)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (891338)