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The complicated interplay between mass and photon transfer within a photocatalytic reactor calls for an integrated design approach. A model-based optimization approach for LED-based photocatalytic reactors is presented. First, a model that describes the distribution of reactants and photons within a photocatalytic reactor is developed. Then, several design variables related to the reactor dimensions and light sources are optimized simultaneously using the photocatalytic degradation of toluene as a model system. The results demonstrate how different formulations of the problem can be used to either minimize the reactor cost or to obtain a specified concentration profile within the reactor.

An optimal photon utilization is important for the economic performance of a photocatalytic reactor. However, for the desired reactor performance, it is often difficult to predict the required photon utilization. In this work, automated feedback and feedforward controllers are investigated to maintain the reactor conversion close to a desired value by adjusting the photon irradiance within a LED-based photocatalytic reactor for toluene degradation. The feedback controller was able to control the conversion during a set-point tracking experiment and was able to mitigate the effects of catalyst deactivation in an automated fashion. The feedforward controller was designed based on an empirical steady-state model to mitigate the effect of changing toluene inlet concentration and relative humidity, which were measured input disturbances. The results demonstrated that feedback and feedforward control were complementary and could mitigate the effects of disturbances effectively such that the photocatalytic reactor operated close to desired conditions at all times. The presented work is the first example of how online analytical technologies can be combined with "smart" light sources such as LEDs to implement automated process control loops that optimize photon utilization. Future work may expand on this concept by developing more advanced control strategies and exploring applications in different areas.

Photocatalysis holds great promise to enable sustainable chemical processes related to, for example, the production of renewable fuels or prevention of pollution through advanced oxidation. However, despite significant progress and continuing interest from academia, industry and policy makers, key challenges have to be overcome. First, ideal photocatalytic materials should obey stringent requirements related to stability, cost, bandgap compatibility, availability of raw materials, and photon efficiency. In spite of certain limitations, such as an undesirable band gap, titania remains the frontrunner in terms of research and commercial applications. This chapter briefly discusses strategies to expand the allowable bandgap of photocatalytic materials. A key focus is on the use of metal–organic frameworks (MOFs). MOFs have an organic–inorganic structure, exhibit a high surface area and can be tuned with tremendous flexibility, which makes them promising candidates to advance photocatalysis. Second, the development of photocatalytic reactors is discussed. The design and operation of photocatalytic reactors is not trivial due to requirements for efficient contact of reactants with the catalyst and efficient utilization of photons. The former requirement is common for any heterogeneous catalytic reactor whereas the latter is unique for photocatalysis. Consequently, numerous reactor configurations have been designed specifically for photocatalysis of which a selection is reviewed in this chapter. Recent advances in simulation and optimization of mathematical models of photocatalytic reactors offer an important support for design. Furthermore, novel solid-state light sources provide opportunities for increased robustness, reduced costs and improved flexibility for the design and operation of future photocatalytic reactors.