Dataset: Active learning streamlines development of high performance catalysts for higher alcohol synthesis

In this repository there are four Excel files. The Master file comprises of all the experimental and computational data complied as a part of the research work titled "Active learning streamlines development of high performance catalysts for higher alcohol synthesis" carried out at the Advanced Catalysis Engineering group, ETHZ. The repository contains three additional files "Modelling_Data_Phase_1", "Modelling_Data_Phase_2", "Modelling_Data_Phase_3" which contain the curated data to run the Gaussian process -Bayesian Optimization algrotihm across three specific active learning Phases devised in this study. The python codes necessary to run the model are housed in GitHub in the link provided below.