(372w) Microkinetic Model Reduction for Ethylene Oligomerization Reactor Optimization and Design
Bottom-up multiscale modeling strategies are predominantly used to predict reactor behavior from microscopic scale calculations . This approach naturally leads to unprecedented accuracy in process design, control, and optimization. It departs significantly from the empirical process design and control strategies of the past, whereby fitting to experimental data was essential to model building. Current efforts are focused on either the molecular scale aspects of microkinetic model development or the process scale aspects including material design for catalysts and reactor design
In this work, we explore the importance of microkinetic model reduction in providing bottom-up and top-down systems analysis for novel shale gas processing technologies. This work is part of the collaborative NSF Center for Innovative and Strategic Transformation of Alkane Resource (CISTAR). We seek to establish strong feedback loops between catalysis, separations, and systems engineering researchers by extracting kinetic insights, and setting reactor-scale selectivity, conversion, and operating condition targets. This poster presents a detailed review of multiscale modeling paradigms for reactor engineering. We then explore application to oligomerization reactor design as part of a modular gas-to-liquids system. We are developing multi-scale optimization frameworks for detailed reactor optimization and intensification that leverages microkinetic modeling , process synthesis , and systems analysis  with CISTAR collaborators to systematically help guide catalyst research and development.
- Salciccioli, M., Stamatakis, M., Caratzoulas, S., & Vlachos, D. G. (2011). A review of multiscale modeling of metal-catalyzed reactions: Mechanism development for complexity and emergent behavior. Chemical Engineering Science, 66(19), 4319-4355.
- Stamatakis, M., & Vlachos, D. G. (2012). Unraveling the complexity of catalytic reactions via kinetic Monte Carlo simulation: current status and frontiers. ACS Catalysis, 2(12), 2648-2663.
- Stamatakis, M. (2014). Kinetic modelling of heterogeneous catalytic systems. Journal of Physics: Condensed Matter, 27(1), 013001.
- Prasad, V., Karim, A. M., Ulissi, Z., Zagrobelny, M., & Vlachos, D. G. (2010). High throughput multiscale modeling for design of experiments, catalysts, and reactors: Application to hydrogen production from ammonia. Chemical Engineering Science, 65(1), 240-246.
- Sutton, J. E., Lorenzi, J. M., Krogel, J. T., Xiong, Q., Pannala, S., Matera, S., & Savara, A. (2018). Electrons to Reactors Multiscale Modeling: Catalytic CO Oxidation over RuO2. ACS Catalysis, 8(6), 5002-5016.
- Partopour, B., & Dixon, A. G. (2018). Integrated multiscale modeling of fixed bed reactors: Studying the reactor under dynamic reaction conditions. Chemical Engineering Journal.
- Raimondeau, S., & Vlachos, D. G. (2002). Recent developments on multiscale, hierarchical modeling of chemical reactors. Chemical Engineering Journal, 90(1-2), 3-23.
- Brydon, R. R., Peng, A., Qian, L., Kung, H. H., & Broadbelt, L. J. (2018). Microkinetic Modeling of Homogeneous and Gold Nanoparticle-Catalyzed Oxidation of Cyclooctene. Industrial & Engineering Chemistry Research, 57(14), 4832-4840.
- Ridha, T., Li, Y., Gençer, E., Siirola, J., Miller, J., Ribeiro, F., & Agrawal, R. (2018). Valorization of Shale Gas Condensate to Liquid Hydrocarbons through Catalytic Dehydrogenation and Oligomerization. Processes, 6(9), 139.
- Pacsi, A. P., Alhajeri, N. S., Zavala-Araiza, D., Webster, M. D., & Allen, D. T. (2013). Regional air quality impacts of increased natural gas production and use in Texas. Environmental science & technology, 47(7), 3521-3527.