Microkinetic,
in situ analytics, and empirical modeling approaches
for developing intrinsic CO2 photoreduction kinetics are
presented in this Perspective. Intrinsic kinetic models that are independent
of photoreactor geometry are critical for scaling CO2 photoreduction
photoreactors. Successfully scaling CO2 photoreduction
is limited using the current extrinsic CO2 photoreduction
kinetic models described in this Perspective, because they are dependent
on the photoreactor geometry and scale used. The impact of different
photoreactor geometries and light transport that lead to extrinsic
kinetic models is reviewed. The impacts of temperature and pressure
on surface diffusion is highlighted as additional important process
parameters. The current Langmuir–Hinshelwood-based kinetic
models are discussed, and their limitations are highlighted, with
respect to modeling the possible deactivation of the photocatalyst.
With a view on developing an intrinsic kinetic model, the challenges
for developing CO2 photoreduction kinetics are highlighted
and discussed with reference to the current extrinsic CO2 photoreduction kinetic model examples found in the literature. Robust
analytical methods for collecting CO2 photoreduction kinetic
data and for confirming the carbon source are discussed. The false
positive production from adventitious carbon and organic impurities
introduced during the synthesis and/or coating of photocatalysts with
solvents and degradation of photoreactor components is highlighted
as a challenge to collecting CO2 photoreduction kinetic
data. It is shown that a wide range of the kinetic model coefficient
values are possible when using a multistart, genetic algorithm, or
particle swarm approach for estimating nonlinear model coefficients.
Finally, an easy to test and implement approach using a mean median
multistart and trust-region reflective algorithm method is presented
for the estimation of nonlinear CO2 photoreduction kinetic
model coefficients.