Simulating favorable adsorption in lithium-ion batteries using a novel cellular-automaton-based method

Abstract

The advances in micro and nano-technologies have increased the demand to study surface effects such as adsorption using novel methods. Cellular automata, being a simple and to some extend intuitive method, seems a great candidate. Here, we have developed a simple adsorption model based on cellular automata to model 'favorable' adsorption isotherms. Using intuitive local rules based on the three common adsorption isotherms, i.e., Langmuir, Elovich, and Hill-Deboer isotherms, the model matched the predicted behavior of these isotherms completely. To further show the power of the model, we analyzed the adsorption of Li-ions on titania. Although we have neglected the absorption in the bulk of the titania, our results are in good accord with the experimental data. This accordance shows that even using a high level of simplification, the model can predict the behavior of a very complicated system such as a Li-ion battery. Therefore, considering the potential of parallelization, ease of calibration with experiments, and modifiability, this model can serve as a suitable computational tool for studying adsorption.

An effective model for sodium insertion in hard carbons

“…However, our effective model helps to clarify the relative contributions of Na on defect sites, and Na adsorbed to graphitic layers to the capacity. The comparison between simulation and Langmuir theory 53 of the 1st cycle is shown in Fig. 11.…”

Influence of Curing Agents Molecular Structures on Interfacial Characteristics of Graphene/Epoxy Nanocomposites: A Molecular Dynamics Framework

“…[41] These methods could offer a meaningful understanding of the system's interactions, leading to fewer trials and errors for experimental parametrizations. [42][43][44][45][46] Using molecular dynamics (MD) simulations combined with a mathematical interpretation of the outputs, Alizadeh Sahraei et al [47] investigated the effect of cross-linking density and the number of graphene layers on the thickness and interaction energy in the interphase. They showed that the crosslinking density and, more precisely, the presence of the crosslinking bonds in the interphase significantly affect the interphase thickness in epoxy nanocomposites.…”

“…[ 41 ] These methods could offer a meaningful understanding of the system's interactions, leading to fewer trials and errors for experimental parametrizations. [ 42–46 ]…”