Experimental and reactive transport modeling study of direct lithium extraction From brines with Li/Al-layered double
Muhammed Rashik Mojid1, Jiahui You1, Kyung Jae Lee1
1Department of Petroleum Engineering, University of Houston, 5000 Gulf Freeway, Building 9, Houston, TX 77204, USA.
Abstract:
The global demand for lithium (Li) has surged in the past decade due to the rapid adoption of Li-ion batteries, particularly in the electrification of transportation. Approximately 70 % of the world's Li is sourced from natural brines, which also contain high concentrations of competing cations such as sodium (Na+), magnesium (Mg2+), and calcium (Ca2+), posing significant challenges for selective Li recovery. This study explores the selective extraction of Li+ from synthetic brines using Li/aluminum (Al)-layered double hydroxides (Li/Al-LDH), addressing a critical gap in the literature. The synthesized Li/Al-LDH was characterized by SEM, EDX, FTIR, XRD, TGA, and BET techniques, confirming its structural, morphological, and surface properties consistent with LDH materials. Li+ adsorption kinetics were evaluated using a pseudo-second-order model, and equilibrium capacities were determined. A novel modeling approach was developed by integrating pseudo-second-order kinetics into a computational fluid dynamics (CFD) framework based on the convection-diffusion and Darcy-Brinkman-Stokes (DBS) equations, enabling predictive simulation of reactive transport during Li recovery from brine, a capability not previously reported. The model showed strong agreement with both analytical flow solutions and experimental adsorption data. Maximum Li+ adsorption capacities of 12.765 mg/g at 25 °C and 18.5 mg/g at 45 °C were achieved. Notably, Li/Al-LDH demonstrated exceptional selectivity for Li+ over competing cations, with a Li+/Mg2+ separation factor reaching 143.47. This integrated experimental and modeling framework offers a promising pathway for optimizing Li extraction from brines, with implications for advancing selective sorbent design and process efficiency in industrial applications.
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