Machine Learning-Based Kinetic Modeling of the CO₂ Methanation Reaction over an Industrial Catalyst.

ABSTRACT: In industrial practice, it is common to use commercially available catalysts to facilitate chemical reactions. Unfortunately, due to the confidential composition and complex properties of the catalysts, a precise understanding of the reaction mechanism and intermediates is often difficult to obtain. This complicates the development of robust kinetic models, delaying an effective reactor design. This raises the question of whether machine learning (ML)-based regressions can reliably describe kinetics without requiring detailed reaction mechanisms. In this work, this research question was addressed by performing kinetic experiments on a commercial Ni/ZrO₂-based CO₂ methanation catalyst (Himetz by Kanadevia Corporation) in an isothermal, fixed bed reactor. A 216-point da

SUBMITTER: Petremand H 

PROVIDER: S-EPMC12532210 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature