Anoop Chakkingal

Efficient Promoters and Reaction Paths in the CO₂ Hydrogenation to Light Olefins over Zirconia-Supported Iron Catalysts

Alan J. Barrios, Deizi V. Peron, Anoop Chakkingal et al. · ACS Catalysis · 2022 · 75 citations

Materials Science, Inorganic Chemistry, Chemical Engineering +14

Multi-output machine learning models for kinetic data evaluation : A Fischer–Tropsch synthesis case study

Anoop Chakkingal, Pieter Janssens, Jeroen Poissonnier et al. · Chemical Engineering Journal · 2022 · 48 citations

Model Optimization, Engineering, Machine Learning +9

Machine learning based interpretation of microkinetic data: a Fischer–Tropsch synthesis case study

Anoop Chakkingal, Pieter Janssens, Jeroen Poissonnier et al. · Reaction Chemistry & Engineering · 2021 · 18 citations · Full text

Engineering, Machine Learning, Data Exploration +18

Unravelling the influence of catalyst properties on light olefin production via Fischer–Tropsch synthesis: A descriptor space investigation using Single-Event MicroKinetics

Anoop Chakkingal, Laura Pirro, Ana R. Costa da Cruz et al. · Chemical Engineering Journal · 2021 · 14 citations · Full text

Materials Science, Chemical Engineering, Catalyst Properties +8

Recent advances in the use of Steady-State Isotopic Transient Kinetic Analysis data in (micro)kinetic modeling for catalyst and process design

Pieter Janssens, Jeroen Poissonnier, Anoop Chakkingal et al. · Catalysis Communications · 2023 · 12 citations · Full text