Modeling CO2 desorption during Li4SiO4 regeneration: comparative analysis of pseudo-steady-state and fully transient shrinking-core models
; Linares, K.M. ; Arturo-Calvache, J. ; Gennari, Fabiana Cristina
; Rodriguez, Maria Laura 
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Fecha
09/2026
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Pergamon-Elsevier Science Ltd
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Chemical Engineering Science
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0009-2509
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Inglés
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Resumen
Lithium orthosilicate (Li4SiO4) is a promising sorbent for high-temperature CO2 capture due to its high theoretical capacity and thermal stability. However, theregeneration stage, involving the reaction between lithium carbonate and lithium metasilicate to release CO2 and reform Li4SiO4, remains poorly understood due tothe intricate coupling of thermodynamics, kinetics, and mass transport. This work presents a theoretical modeling and simulation study of CO2 desorption fromLi4SiO4 pellets using an unreacted shrinking-core model (SCM). The objective is to develop a mechanistically consistent framework that resolves CO2 generation,intraparticle diffusion, and external mass transfer. The study involves: (i) a fully transient (FT) shrinking-core model accounting for transient CO2 accumulation,contrasted with a pseudo-steady-state (PSS) approximation; (ii) validation against literature experimental data; and (iii) parametric simulation to evaluate the effectsof temperature, CO2 partial pressure, pellet size, and total pressure on desorption dynamics.Simulation results reveal substantial discrepancies between PSS and FT predictions. At 720 ◦C, the FT model predicts complete desorption in ~1300 s, whereas thePSS model estimates ~2200 s. Higher temperatures enable near-complete calcination (α = 0.99 in under 2000 s), while elevated bulk CO2 pressure limits desorptionextent (α = 0.6 at 0.3 atm). Damk¨ohler number analysis (Da = 10–270) confirms diffusion-limited regimes, justifying the FT formulation. Pellet geometry also plays acritical role: larger radii increase reactant availability but exacerbate internal diffusion resistance. Overall, this study provides a mechanistically consistentframework for modeling CO2 desorption and offers a predictive tool for optimizing high-temperature CO2 capture processes.
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