Probability Langmuir-Hinshelwood based CO₂ photoreduction kinetic models

For engineering solutions, scaling photoreactors and processes, kinetic models that describe the impact of process conditions on CO₂ photoreduction are critical to driving this technology forward. Probability Langmuir-Hinshelwood based CO₂ photoreduction kinetic models were developed after several criteria that included: a high purity photodifferential photoreactor with a high ratio of reagent gas volume to irradiated photocatalyst surface area and automated robust data collection and kinetic modelling using a MATLAB programme. Product distribution profiles indicated the dynamic changes occurring over the photocatalyst with an initial increase in H₂ product distribution, followed by an increase in CH₄ and finally CO product distribution, possibly due to the photocatalytic degradation of CH₂O and CH₂O₂ intermediates. Production of H₂ increased with a decrease in CH₄ when the partial pressure of H₂O was increased. Using the glyoxal mechanism, this is possibly explained via the formation of CH₃CO₂H from H₂O reacting with CH₃CHO that prevents the full conversion of CH₃CHO to CH₄. To account for deactivation, probability Langmuir–Hinshelwood based kinetic models were used to fit CO₂ photoreduction kinetic data for CH₄, CO and H₂ with low average standard errors of 3.44×10^-4,1.54×10^-4 and 1.36×10^-4, respectively. The probability LH based kinetic model coefficients were estimated with low standard deviations, using a robust and repeatable numerical method using a trust-region and multi-start algorithm. The models were used to predict optimised selectivity of CH₄, CO and H₂.