Advanced computational strategies for lithium chemical and electrochemical adsorption: A comprehensive state-of-the-art review
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abstract
The extraction of lithium resources through chemical and electrochemical adsorption has become increasingly vital to meet the growing demands of new energy sources. In the adsorption process, computational strategies have been proven indispensable in elucidating the microscopic mechanisms and quantum properties underlying lithium adsorption. While experimental studies on lithium adsorption have advanced significantly, the underlying mechanisms are not yet fully understood. Herein, this review presents recent advancements in computational methods, including Molecular Dynamics (MD), Monte Carlo (MC) simulations, Density Functional Theory (DFT), COMSOL Multiphysics, and Machine Learning (ML), as applied to both chemical and electrochemical lithium adsorption and related materials. The review delves into the principles and methodologies of these approaches, showcasing their effectiveness in optimizing material design and predicting properties. Furthermore, the review highlights these computational strategies in analyzing kinetic and thermodynamic behaviors, studying phase transitions, and tracing flux migration trajectories. Finally, this review evaluates the strengths and limitations of different computational strategies and outlines future research directions. Comprehensively, this review not only provides an insightful understanding of simulation methods for lithium adsorption, but also inspires further upgrade of integrated computational strategies in this field.
