(192f) Multi Objective Optimization of a Photo-Catalytic CO2 Utilization Process

Carbon dioxide, one of the major greenhouse gases, contributes to over 60% of the global warming. While many technologies are being developed for CO₂ utilization, photocatalytic reduction is a promising technology. Photocatalytic reduction of CO₂, also known as artificial photosynthesis, have been investigated for carbon sequestration and production of fuels using solar energy [1]. Experimental evaluation of photo-reactors using different catalysts has been undertaken by many researchers [2]. Mathematical models of photoreactors have also been developed [3–4]. However, the low efficiency of conversion of CO₂ in these reactors, low photo-efficiency, and very low concentration of products are some of the key issues inhibiting commercial viability of this technology. The performance of the photocatalytic reactors can be improved by developing improved photo-catalysts, reactor designs as well as by optimizing operating conditions [5]. While optimization of the radiation/concentration field of generic photocatalytic reactors has been studied by some authors [6-7], optimization of the reactor designs and its operating conditions for photocatalytic CO₂ utilization has not been undertaken yet.

A partial differential algebraic equation (PDAE) model of a multichannel optical fiber monolithic reactor model with TiO₂-coated optical fiber is developed by incorporating the Langmuir Hinshelwood model for describing the reaction kinetics, a submodel for describing the flow characteristics through the channels, and an empirical radiation field submodel. The PDAE model is discretized in space and used for optimization using a nonlinear programming solver.

Several decision variables are considered for optimization. At low velocities, the single pass conversion can be improved [4], but a low velocity reduces throughput from the reactor. On the other hand, if the velocity is increased, the throughput increases but due to lower single pass conversion, concentration of the product decreases thus increasing the parasitic energy loss for separation. Flow configuration through the reactor also affects the conversion efficiency [4]. Upflow through the channel leads to higher conversion efficiency due to the annular flow characteristic in comparison to the downflow especially at low velocities where it exhibits film flow leading to reduction in the incidence light. However, the upflow leads to higher pumping cost. Higher light intensity can improve the single pass conversion, but that reduces the overall photo-energy efficiency. In addition to the decision variables noted above, reactor design parameters such as the optical fiber diameter, monolith channel wall diameter, reactor length and operating parameters such as the fluid velocity, CO₂ concentration, and other design parameters such as the input light intensity are optimized. There are tradeoffs among various objectives for this system. If the conversion of CO₂ has to be improved, photo-efficiency will deteriorate for the same reactor with same catalysts. Therefore a, multiobjective optimization problem is solved that can maximize the conversion and photo-efficiency. The multiobjective optimization problem is solved by a goal-programming approach [8]. Sensitivity to catalytic properties and diffusivity properties are evaluated for analyzing diffusion limited vs reaction limited regions thus providing future research direction for improving the economics of the photocatalytic conversion of CO₂.

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. Applied Catalysis B: Environmental 31 (2001) pp. 209–220.

[3] Wang, T.; Yang, L.; Du, X.; Yang, Y. Numerical Investigation on CO2 Photocatalytic Reduction in Optical Fiber Monolith Reactor. Energy Convers. Manage. 2013, 65, 299−307.

[4] Hongfei Lin and Kalliat T. Valsaraj, an Optical Fiber Monolith Reactor for Photocatalytic Wastewater Treatment. AIChE Journal, 52 (2006), pp. 2271-2280.

[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.

[6] Maniraj Singh, Ignasi Salvado´-Estivill, and Gianluca Li Puma, Radiation Field Optimization in Photocatalytic Monolith Reactors for Air Treatment. AIChE J, 53(2007): 678–686.

[7] Fei Cao, Huashan Li, Hailiang Chao, Liang Zhao, Liejin Guo, Optimization of the concentration field in a suspended photocatalytic reactor. Energy, 74 (2014): pp. 140-146.

[8] Collette, Y.; Siarry, P. Multiobjective Optimization: Principles and Case Studies; Springer: New York, 2003.