Geometry Optimization for Multi-Inlet Vortex Photoreactor for CO2 Reduction

Authors

  • Jesús Valdés Universidad Autónoma de Querétaro
  • Jorge Luis Domínguez-Juárez
  • Rufino Nava
  • Ángeles Cuán
  • Carlos Martín Cortés-Romero

DOI:

https://doi.org/10.31349/RevMexFis.68.020601

Keywords:

Genetic Algorithm, Residence Time, Turbulence Intensity, Computational Fluid Dynamics

Abstract

Process optimization of multiphase chemical and/or photochemical reactor means a challenge not only at laboratory scale but also while scaling-up is intended towards industrial applications. Using computational tools, such as Computational Fluid Dynamics, is essential to assess transport limitations of the heterogeneous process to verify the kinetic regime while the reaction and the reactor engineering are studied. Computational Fluid Dynamics, together with Genetic Algorithms, has been currently applied to verify fluid behavior and turbulence. The latter device has been self-designed and is planned to be constructed for CO2 reduction. The results of the Computational Fluid Dynamics simulations are presented and discussed, in order to optimize reactor operation of a multi-inlet vortex photoreactor. By considering the catalytic particle features, the residence time distribution in the multi-inlet photoreactor has been verified and optimized.

References

Betts, R.A.; Jones, C.D.; Knight, J.R.; Keeling, R.F.; Kennedy, J.J. El Niño and a record CO2 rise. Nature Climate Change (2016), 6, pp. 806–810. doi: https://doi.org/10.1038/nclimate3063.

Core Writing Team, R.K.P.; (eds.), L.A.M. IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC Geneva, Switzerland, 2014.

Looney, B. Statistical Review of World Energy, 2020, 2020.

Mustafa, A.; Lougou, B.G.; Shuai, Y.; Wang, Z.; Tan, H. Current technology development for CO2 utilization into solar fuels and chemicals: A review. Journal of Energy Chemistry 2020, 49, pp. 96–123. doi: https://doi.org/10.1016/j.jechem.2020.01.023.

Zhang, S.; Fan, Q.; Xia, R.; Meyer, T.J. CO2 reduction: from homogeneous to heterogeneous electrocatalysis. Accounts of chemical research 2020, 53, pp. 255–264. doi: https://doi.org/10.1021/acs.accounts.9b00496.

Zhao, G.; Huang, X.; Wang, X.; Wang, X. Progress in catalyst exploration for heterogeneous CO 2 reduction and utilization: a critical review. Journal of Materials Chemistry A 2017, 5, pp. 21625–21649. doi: https://doi.org/10.1039/c7ta07290b.

Schneider, J.; Jia, H.; Muckerman, J.T.; Fujita, E. Thermodynamics and kinetics of CO2, CO, and H+ binding to the metal centre of CO2 reduction catalysts. Chemical Society Reviews 2012, 41, pp. 2036–2051. doi: https://doi.org/10.1039/c1cs15278e.

Zhou, Y.J.; Kerkhoven, E.J.; Nielsen, J. Barriers and opportunities in bio-based production of hydrocarbons. Nature Energy 2018, 3, pp. 925–935. doi: https://doi.org/10.1038/s41560-018-0197-x.

Adarsh, K.S.; Chandrasekaran, N.; Chakrapani, V. In-situ spectroscopic techniques as critical evaluation tools for electrochemical carbon dioxide reduction: a mini review. Frontiers in chemistry 2020, 8, pp. 137. doi: https://doi.org/10.3389/fchem.2020.00137.

Lee, M.Y.; Park, K.T.; Lee, W.; Lim, H.; Kwon, Y.; Kang, S. Current achievements and the future direction of electrochemical CO2 reduction: A short review. Critical Reviews in Environmental Science and Technology 2020, 50, pp. 769–815. doi: https://doi.org/10.1080/10643389.2019.1631991.

Gong, J.; Li, C.; Wasielewski, M.R. Advances in solar energy conversion. Chemical Society Reviews 2019, 48, pp. 1862–1864. doi: https://doi.org/10.1039/c9cs90020a.

Lewis, N.S. Toward cost-effective solar energy use. science 2007, 315, pp. 798–801. doi: https://doi.org/10.1126/science.1137014.

Vu, N.N.; Kaliaguine, S.; Do, T.O. Plasmonic Photocatalysts for Sunlight-Driven Reduction of CO2: Details, Developments, and Perspectives. ChemSusChem 2020, 13, pp. 3967–3991. doi: https://doi.org/10.1002/cssc.202000905.

Li, K.; Peng, B.; Peng, T. Recent advances in heterogeneous photocatalytic CO2 conversion to solar fuels. ACS Catalysis 2016, 6, pp. 7485–7527. doi: https://doi.org/10.1021/acscatal.6b02089.

Green, M.A.; Bremner, S.P. Energy conversion approaches and materials for high-efficiency photovoltaics. Nature materials 2017, 16, pp. 23–34.

Zhu, S.; Wang, D. Photocatalysis: basic principles, diverse forms of implementations and emerging scientific opportunities. Advanced Energy Materials 2017, 7, pp. 1700841. doi: https://doi.org/10.1002/aenm.201700841.

Shi, R.; Chen, Y. Controlled formation of defective shell on TiO2 (001) facets for enhanced photocatalytic CO2 reduction. ChemCatChem 2019, 11, pp. 2270–2276. doi: https://doi.org/10.1002/cctc.201900061.

Li, K.; Teng, C.; Wang, S.; Min, Q. Recent advances in TiO2-based heterojunctions for photocatalytic CO2 reduction with water oxidation: A review. Frontiers in Chemistry 2021, 9. doi: https://doi.org/10.3389/fchem.2021.637501.

Ochedi, F.O.; Liu, D.; Yu, J.; Hussain, A.; Liu, Y. Photocatalytic, electrocatalytic and photoelectrocatalytic conversion of carbon dioxide: a review. Environmental Chemistry Letters 2020, pp. 1–27. doi: https://doi.org/10.1007/s10311-020-01131-5.

Zeng, S.; Kar, P.; Thakur, U.K.; Shankar, K. A review on photocatalytic CO2 reduction using perovskite oxide nanomaterials. Nanotechnology 2018, 29, pp. 052001. doi: https://doi.org/10.1088/1361-6528/aa9fb1.

Kistler, T.A.; Larson, D.; Walczak, K.; Agbo, P.; Sharp, I.D.; Weber, A.Z.; Danilovic, N. Integrated Membrane-Electrode-Assembly Photoelectrochemical Cell under Various Feed Conditions for Solar Water Splitting. Journal of The Electrochemical Society 2018, 166, pp. H3020. doi: https://doi.org/10.1149/2.0041905jes.

Kim, H.R.; Razzaq, A.; Heo, H.J.; In, S.I. Photocatalytic conversion of CO 2 into hydrocarbon fuels with standard titania (Degussa P25) using newly installed experimental setup. Rapid Communication in Photoscience 2013, 2, pp. 64–66. doi: https://doi.org/10.5857/rcp.2013.2.2.64.

Ali, S.; Flores, M.C.; Razzaq, A.; Sorcar, S.; Hiragond, C.B.; Kim, H.R.; Park, Y.H.; Hwang, Y.; Kim, H.S.; Kim, H.; others. Gas phase photocatalytic CO2 reduction,“A brief overview for benchmarking”. Catalysts 2019, 9, pp. 727. doi: https://doi.org/10.3390/catal9090727.

Mazierski, P.; Bajorowicz, B.; Grabowska, E.; Zaleska-Medynska, A. Photoreactor design aspects and modeling of light. In Heterogeneous photocatalysis; Springer, 2016; pp. 211–248.

Dilla, M.; Schlögl, R.; Strunk, J. Photocatalytic CO2 Reduction Under Continuous Flow High-Purity Conditions: Quantitative Evaluation of CH4 Formation in the Steady-State. ChemCatChem 2017, 9, pp. 696–704. doi: https://doi.org/10.1002/cctc.201601218.

Simon, D. Evolutionary optimization algorithms; John Wiley & Sons, 2013.

Goldberg, D.E.; Holland, J.H. Genetic algorithms and machine learning 1988. doi: https://doi.org/10.1145/168304.168305.

De Jong, K.A. Analysis of the behavior of a class of genetic adaptive systems. Technical report, 1975.

Johnson, J.M.; Rahmat-Samii, Y. Genetic algorithm optimization and its application to antenna design. Proceedings of IEEE Antennas and Propagation Society International Symposium and URSI National Radio Science Meeting. IEEE, 1994, Vol. 1, pp. 326–329.

Casado, C.; Marugán, J.; Timmers, R.; Muñoz, M.; van Grieken, R. Comprehensive multiphysics modeling of photocatalytic processes by computational fluid dynamics based on intrinsic kinetic parameters determined in a differential photoreactor. Chemical Engineering Journal 2017, 310, pp. 368–380. doi: https://doi.org/10.1016/j.cej.2016.07.081.

Dedeyne, J.N.; Geerts, M.; Reyniers, P.A.; Wéry, F.; Van Geem, K.M.; Marin, G.B. Computational fluid dynamics-based optimization of dimpled steam cracking reactors for reduced CO2 emissions. AIChE Journal 2020, 66, pp. e16255. doi: https://doi.org/10.1002/aic.16255.

Akram, M.T.; Kim, M.H. CFD Analysis and Shape Optimization of Airfoils Using Class Shape Transformation and Genetic Algorithm—Part I. Applied Sciences 2021, 11, pp. 3791. doi: https://doi.org/10.3390/app11093791.

Norton, T.; Sun, D.W. Computational fluid dynamics (CFD)–an effective and efficient design and analysis tool for the food industry: a review. Trends in Food Science & Technology 2006, 17, pp. 600–620. doi: https://doi.org/10.1016/j.tifs.2006.05.004.

Dixon, A.G.; Nijemeisland, M. CFD as a design tool for fixed-bed reactors. Industrial & Engineering Chemistry Research 2001, 40, pp. 5246–5254. doi: https://doi.org/10.1021/ie001035a.

Kulkarni, S.R.; Vandewalle, L.A.; Gonzalez-Quiroga, A.; Perreault, P.; Heynderickx, G.J.; Van Geem, K.M.; Marin, G.B. Computational fluid dynamics-assisted process intensification study for biomass fast pyrolysis in a gas–solid vortex reactor. Energy & Fuels 2018, 32, pp. 10169–10183. doi: https://doi.org/10.1002/aic.16255.

Lee, D.S.; Amara, Z.; Clark, C.A.; Xu, Z.; Kakimpa, B.; Morvan, H.P.; Pickering, S.J.; Poliakoff, M.; George, M.W. Continuous photo-oxidation in a vortex reactor: efficient operations using air drawn from the laboratory. Organic process research & development 2017, 21, pp. 1042–1050.

Van Rossum, G.; Drake Jr, F.L. Python tutorial; Vol. 620, Centrum voor Wiskunde en Informatica Amsterdam, 1995.

Schlichting, H.; Truckenbrodt, E. Aerodynamik des Flugzeuges Grundlagen aus der Strömungsmechanik Aerodynamik des Tragflügels (Teil I) 1959.

Lam, C. K. G. and Bremhorst, K.. A modified form of the k- model for predicting wall turbulence 1981. doi: https://doi.org/10.1115/1.3240815.

Liu, Z.; Passalacqua, A.; Olsen, M.G.; Fox, R.O.; Hill, J.C. Dynamic delayed detached eddy simulation of a multi-inlet vortex reactor. AIChE Journal 2016, 62, pp. 2570–2578. doi: https://doi.org/10.1002/aic.15230.

Fang, R.H.; Chen, K.N.H.; Aryal, S.; Hu, C.M.J.; Zhang, K.; Zhang, L. Large-scale synthesis of lipid–polymer hybrid nanoparticles using a multi-inlet vortex reactor. Langmuir 2012, 28, pp. 13824–13829. doi: https://doi.org/10.1021/la303012x.

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Published

2022-03-01

How to Cite

[1]
J. Valdés, J. L. Domínguez-Juárez, R. Nava, Ángeles Cuán, and C. M. Cortés-Romero, “Geometry Optimization for Multi-Inlet Vortex Photoreactor for CO2 Reduction”, Rev. Mex. Fís., vol. 68, no. 2 Mar-Apr, pp. 020601 1–, Mar. 2022.

Issue

Vol. 68 No. 2 Mar-Apr (2022): Revista Mexicana de Física

Section

06 Fluid Dynamics

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Copyright (c) 2022 Jesús Valdés, Jorge Luis Domínguez-Juárez, Rufino Nava, Ángeles Cuán, Carlos Martín Cortés-Romero

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