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• W4386224439 abstract "Experimental data driven calibration and reactor sensitivity analysis is a feasible route toward efficient and sustainable CO2 utilization. A feasible approach was developed and implemented to model and simulate the direct conversion of CO2 and H2 to methanol through the direct utilization of experimental data. This approach is widely applicable to any reaction and reactor type. Monolithic reactors, showing lower mass transfer resistance than conventional packed bed reactors, were chosen specifically in this study. This novel technique allows for expedited calibration of experimentally acquired lab data into kinetic, equilibrium, and adsorption parameters for a wide variety of reactions. Such a technique was used in this paper to generate a monolithic reactor model. Simulations based on the generated model were used to study internal and external mass transport in the monolithic reactor. Catalyst layer simulation showed no diffusion limitation between 100 and 300 °C while the external mass transfer coefficient of 0.25 m·s–1 signifies reasonably low external mass transfer resistance. Sensitivity analysis show that circular channel shape offers the highest average Sherwood number (Sh = 6.27 @ 300 °C) while a triangular channel shape provides the highest surface area (SA = 45.6 mm2) at constant volume among other channel shapes with constant cross-sectional area, wall thickness, and channel length. Moreover, a channel hydraulic diameter of 0.4 mm with a channel length of 5 cm was found to be the most optimal for this type of reactor. Lastly, the fine-tuned channel shape and channel length provided the best velocity gradient and residence time for high yield." @default.
• W4386224439 created "2023-08-29" @default.
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• W4386224439 date "2023-08-28" @default.
• W4386224439 modified "2023-09-30" @default.
• W4386224439 title "Modeling and Simulation Based Parametric Analysis for Monolithic CO₂ Hydrogenation Reactors Using Experimental Data" @default.
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• W4386224439 doi "https://doi.org/10.1021/acs.iecr.3c01618" @default.
• W4386224439 hasPublicationYear "2023" @default.
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