Machine learning based interpretation of microkinetic data: a Fischer–Tropsch synthesis case study
Anoop Chakkingal, Pieter Janssens, Jeroen Poissonnier, Alan J. Barrios, Mirella Virginie, Andreï Y. Khodakov, Joris Thybaut
Abstract
A systematic approach for analysing kinetic data and identifying hidden trends using interpretation techniques in data science with the ANN.
Topics & Concepts
Fischer–Tropsch processInterpretation (philosophy)Computer scienceArtificial intelligenceChemistryOrganic chemistryCatalysisSelectivityProgramming languageMachine Learning in Materials ScienceProcess Optimization and IntegrationCatalysis and Oxidation Reactions