Photocatalysis involves the absorption of photons by a semiconductor to enhance chemical reactions. Examples of important applications include the degradation of hazardous chemicals, reduction of carbon dioxide to valuable chemicals and (partial) oxidation of hydrocarbons. Despite many successful demonstrations of this technology at lab-scale, its industrial application has been hindered by the low overall efficiency of the process due to several challenges that need to be resolved. One of the main challenges is efficient utilization of light within a photocatalytic reactor, which affects the economic feasibility of the process especially when using artificial light sources. In the last few years, the feasibility of using UV-LEDs as an alternative light source for conventional UV-lamps, such as mercury and xenon lamps, has been shown for applications in the gas and liquid phase. Yet, strategies that would allow for optimal light utilization within LED-based reactors during design and operation are lacking. Therefore, the focus of this thesis is on the efficient use of photons by development and validation of novel approaches for the design, optimization, and control of LED-based photocatalytic reactors. The photocatalytic degradation of toluene in the gas phase is adopted as the model reaction, since toluene is one of the most common indoor pollutants threatening human health. In the design phase of a LED-based reactor, the flexible positioning of LEDs enabled by their small size, in combination with the reactor design parameters, provides a large degree of freedom. When using all of those degrees of freedom simultaneously, mathematical optimization techniques are a necessity. Hence, a model-based approach for optimization of the design of LED-based photocatalytic reactors is developed. A photocatalytic reaction rate is not only a function of the chemical species adsorbed on the catalytic surface, but also on the rate of photons absorbed by the catalyst. Therefore, an efficient photocatalytic reactor design optimizes both the mass transfer as well as the photon transfer. First, an integrated model is developed that describes the distribution of reactants and photons within an annular LED-based photocatalytic reactor. Second, an objective function, representing a trade-off between capital and operating costs is defined and several design variables related to the reactor dimensions and light sources are optimized simultaneously. Furthermore, the capability of the LED-based photocatalytic reactor in controlling the local reaction rate is shown by changing the objective function of the optimization problem. The results demonstrate the importance of model-based optimization to systematically incorporate the inherent trade-offs that exist in the design and operation of LED-based photocatalytic reactors. A validated process model is essential for optimization. Furthermore, characterization of process trends is needed when developing operational strategies such as automated control. For this purpose, a mini-pilot plant including an annular LED-based photocatalytic reactor has been developed to validate the integrated process model including a radiation field, reaction kinetics, and material balances experimentally for the photocatalytic degradation of toluene. Because water is inevitably present in many photocatalytic applications, a special focus is on the effect of water on reaction kinetics, toluene conversion, mineralization, and catalyst deactivation for characterization of the process trend. The results from parameter estimation studies demonstrate that a competitive reaction rate model can best describe the experimental data with varying water concentration. Furthermore, experimental results demonstrate that toluene conversion is highest at a low water concentration; however, mineralization and catalyst lifetime are enhanced by the presence of water. The validation of the integrated process model and understanding of the role of water allow for improved design and operation of future LED-based photocatalytic reactors. Following the conclusion from the process characterization study that electron-hole recombination is dominant in the system, the impact of periodical illumination of LEDs on the photonic efficiency of toluene degradation is investigated. It has been suggested that intermittent introduction of photons on the catalytic surface can possibly reduce the electron-hole recombination and, consequently, can improve the photon utilization of the photocatalytic process during operation. Therefore, the impact of light/dark periods and duty cycles is studied. However, no transition or change in the photonic efficiency when moving from a short to a long light/dark time at a fixed duty cycle is observed experimentally for the system studied in this thesis. Furthermore, the results of the experiments at two different periods show an increase in photonic efficiency with a decrease in the duty cycle. However, the photonic efficiency under controlled periodic illumination, regardless of the duty cycle or period, is found to be similar to that under continuous illumination at an equivalent average irradiance, suggesting no mass-transfer limitations in the system. Therefore, it is concluded that periodical illumination does not improve photon utilization in a system where electron-hole recombination is dominant but there is no mass transfer limitation. During operation, the performance of an optimally designed reactor may deviate from optimal conditions because of design uncertainties and disturbances acting on the system. Therefore, the application of automated feedback and feedforward controllers to maintain the reactor conversion close to a desired value by adjusting the photon irradiance within a LED-based photocatalytic reactor is studied. The excellent capability of the feedback controller in tracking different conversion set points is shown in the presence of unmeasured and measured disturbances, which allows for a desired conversion of toluene to be maintained. Furthermore, a feedforward controller has been designed based on an empirical steady-state model to mitigate the effect of changing toluene inlet concentration and relative humidity, which are typical measured input disturbances. The results demonstrate that the feedback and feedforward controllers are complementary and can mitigate the effects of disturbances effectively such that the photocatalytic reactor operates close to the desired output at all times. This study delivers 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. This thesis focuses on the development and validation of methods that provide optimal photon utilization within an annular LED-based photocatalytic reactor for design and operation. However, the proposed approaches and findings of this work can in principle be applied to different configurations of LED-based photocatalytic reactors as well. In addition, the suggested mathematical model in this thesis can be applied as a useful tool for the prediction of mass and photon transfer rate during scale-up studies of LED-based photocatalytic reactors. Furthermore, the developed control structures can be transferred to a larger scale since control structures are generally known to scale-up well. Providing approaches for optimum photon utilization, the outcome of this thesis could facilitate the realization of more economically viable photocatalytic processes when transferring the technology from lab-scale to the industrial applications.@en

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. @en

The design and operation of reactors for photocatalytic degradation of organic pollutants remains challenging due to the complex interplay of photon, mass, and heat transfer. An integrated process model including a radiation field, reaction kinetics, and material balances of an annular LED-based photocatalytic reactor for photocatalytic degradation of toluene is validated using experimental data from a mini-pilot plant. A particular emphasis is on the effect of water on reaction kinetics, toluene conversion, mineralization, and catalyst deactivation, which is currently not well understood. The results from parameter estimation demonstrate that a competitive reaction rate model describes the experimental data with varying water concentration best. Furthermore, experimental trends demonstrate that toluene conversion is highest at low water concentrations, however, mineralization and catalyst lifetime are enhanced by the presence of water. The validation of the integrated process model and understanding of the role of water allow for improved design and operation of future photocatalytic reactors.

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The influence of product shape selectivity on the bifunctional conversion of n-C₇ by zeolite catalysts is investigated. Three different zeolite catalysts with different pore sizes (MFI-type, MEL-type, and BEA-type zeolites) have been investigated experimentally. For all three catalysts, n-C₇ is isomerized to monobranched isomers which are further isomerized into dibranched isomers, and these dibranched molecules are converted into cracking products. More dibranched isomers and less cracking products are produced by BEA-type zeolite compared to MFI-type and MEL-type zeolites and clear differences are observed in the distribution of dibranched isomers produced by different catalysts. Molecular simulation is used to compute the adsorption isotherms and free energy barriers for diffusion of dibranched isomers in MFI-type, MEL-type, and BEA-type zeolites. Combining simulation results and experimental observations, it is shown that product shape selectivity can explain the distribution of dibranched molecules while transition state shape selectivity fails to do so. For the medium-pore zeolites (MFI-type and MEL-type zeolites), free energy barriers for diffusion of dibranched molecules are significant. For MFI-type and MEL-type zeolites, the dibranched molecule that has to overcome lower diffusion barrier is produced with a higher yield and the distribution of dimethylpentane molecules is determined by their diffusion rate. It is shown that there is almost no free energy barrier for the diffusion of any of these molecules in BEA-type zeolite. As BEA-type zeolite imposes no free energy barrier for diffusion of any of dibranched isomers, the distribution of dibranched isomers is very close to the equilibrium distribution in the gas phase. Due to the limited mobility of dimethylpentanes within the pores of MFI-type and MEL-type zeolites, most of the dimethylpentane molecules are trapped inside the zeolite and undergo consecutive cracking. Dimethylpentane molecules diffuse sufficiently fast in the large pores of BEA-type zeolite and transfer to the gas phase, before consecutive reaction converts these molecules into cracking products. Moreover, the effect of the MFI-type crystal size on the production of dibranched isomers is investigated. The yield of dibranched isomers reduces by increasing the size of the crystal and larger part of dibranched isomers are cracked as the crystal size of MFI-type is increased.

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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.chemistry has been investigated for nearly thirty years with many notable results being published on apparent process enhancement due to microwave exposure. Conclusive proof of beneficial microwave-chemical interactions is lacking though, as are design rules for successful implementation of microwave-chemical processing systems. In this chapter, the main cause for this is asserted to be the current absence both of suitable instrumentation for research, and processing equipment that merges chemistry with electromagnetic aspects. Several concepts are presented to show how these challenges may be addressed.@en

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.

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