(707f) Multi Objective Optimization of a Photo Catalytic CO2 Utilization Process

Today, thanks to the uncontrolled increase in the world population and a furious consumption of fossil fuels, global warming has increased alarmingly. Limiting the emission of the greenhouse gases has become the call to action for every citizen in this world. Carbon dioxide, one of the major greenhouse gases contributes to over 60% of the global warming. Therefore many methods have been developed recently to capture CO₂ and photocatalytic reduction is emerging to be a promising solution to control the level of CO₂ emissions. Several scholars have studied and made inroads researching artificial photo synthesis as a novel idea to develop technologies like generating electricity without pollution, carbon sequestration and production of fuels using solar energy [1]. Several photo-reactors have also been developed and their performance have been evaluated experimentally [2]. Mathematical models have also been developed where it has been found that the numerical performance has matched with the experimental results.[3] – [4] The main cause of concern is the low efficiency of these reactors which has posed as a daunting roadblock for this method to be considered as a viable option to replace the existing processes. The performance of the photocatalytic process can be improved either by developing a new photo-catalyst or improving the design of photo-reactors [5]. Optimization of parameters to improve the performance of the photocatalytic reactors have also been studied [6]-[7]. These papers talk about how the performance of the photon absorption changes with respect to some parameter. However, none of these papers talk about the tradeoffs that need to be considered by varying these parameters.

In this paper, we develop an optimization model for a multichannel optical fiber monolithic reactor which has been experimentally investigated. The main objective is to optimize the parameters so that the efficiency of the reactor is maximized. In this model, we will be incorporating the Langmuir Hinshelwood kinetics submodel, an annular flow dynamics sub model and an empirical radiation field submodel. We plan to carry out a multi objective optimization for this model where we will be optimizing multiple parameters to maximize the conversion of the reactor while also making sure that the total cost to run the reactor is at a minimum.

In Hongfei Lin et al. [4], they study how by varying the velocity, the single pass conversion changes. From figure 4, we can see that at low velocities, the single pass conversion is the highest. But they fail to take into account that at low velocity, the amount of reactant that we will be passing through will be lesser, hence the operating costs will increase as very less product is formed in one single pass. However if we pass the feed stream at higher velocity, more product will be formed but, it will be heavily diluted as the amount of reactant we are passing through is much higher. Hence, the cost of separation will be higher in this case. Therefore, there is a trade off in both cases that we need to account for while designing the reactor. From the graph, we can deduce that while the velocity increases by 7 times (~5 to around 35 cm/min), the single pass conversion decreases only by ~3times. If we don’t take the cost factor into account, we can bluntly speculate that running the reactor at high velocity will be beneficial. Continuing on the same path, in figure 9 we can see how the direction of the flow affects the single pass removal efficiency. While upflow certainly performs better than downflow especially at low velocities, the upflow comes with an additional baggage as we need to account for the cost of pumping the feed whereas for downflow, gravity does the job for us. Now to take another instance, in figure 5, we can see that at higher light intensities, the single pass conversion increases. But, for higher intensities we will be using more wattage power and hence the cost increases too. Now, looking at figure 3, we can take the reaction kinetics as either reaction limited or diffusion limited. If the rate of the reaction is dependent on the rate controlling step, modifying/improving the catalyst can increase the reaction rate. But, if it is diffusion limited, changing the catalyst won’t significantly improve the reaction rate and alternatives need to be considered like changing the solvent. By optimizing all these parameters and taking such tradeoffs into consideration, we can maximize the efficiency of these reactors while also keeping in mind that the cost associated needs to be minimized. We may also be able to speculate and describe the properties of a utopian catalyst that can replicate the performance in real life which can be useful while choosing or developing a new photo catalyst.

References

[1] Pace RJ. An integrated artificial photosynthesis model, artificial photosynthesis. Wiley-VCH Verlag GmbH & Co. KGaA; 2006. p. 13–34.

[2] Wonyong Choi∗, Joung Yun Ko, Hyunwoong Park, Jong Shik Chung, Investigation on TiO2-coated optical fibers for gas-phase photocatalytic oxidation of acetone.

[3] Tianchen Wang, Lijun Yang, Xiaoze Du, Yongping Yang, Numerical investigation on CO2 photocatalytic reduction in optical fiber monolith reactor.

[4] Hongfei Lin and Kalliat T. Valsaraj, an Optical Fiber Monolith Reactor for Photocatalytic Wastewater Treatment.

[5] M. Tahir, N.A.S. Amin, Photo-induced CO2 reduction by hydrogen for selective CO evolution in a dynamic monolith photoreactor loaded with Ag-modified TiO2 nanocatalyst, Int. J. Hydrogen Energy 42 (23) (2017) 15507–15522, https://doi.org/10.1016/j.ijhydene.2017.05.039).

[6] Maniraj Singh, Ignasi Salvado´-Estivill, and Gianluca Li Puma, Radiation Field Optimization in Photocatalytic Monolith Reactors for Air Treatment.

[7] Fei Cao, Huashan Li, Hailiang Chao, Liang Zhao, Liejin Guo, Optimization of the concentration field in a suspended photocatalytic reactor.