A cellular automata framework to study the diffusion in single and binary solvent systems

Abstract In this work, we present a two-dimensional cellular automata (CA) model to study mass transfer by diffusion of molecules in single and binary solvent systems. The method builds on Vanag’s probabilistic cellular automata (PCA), where diffusion is simulated through stochastic exchange of molecules between neighboring cells. While the original PCA framework effectively models single component diffusion driven by concentration gradients, it could not account for variable diffusion coefficients. We address this limitation by generalizing the PCA approach to handle binary systems, enabling the simulation of diffusion in heterogeneous materials with varied transport properties. This extension broadens the applicability of CA-based methods for capturing complex diffusion dynamics.

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Publication Details

Journal
Scientific Reports
Published
2026-10-06
DOI
https://doi.org/10.1038/s41598-026-69251-6
Primary Topic
Cellular Automata and Applications
Type
article
Field-Weighted Citation Impact
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article

A cellular automata framework to study the diffusion in single and binary solvent systems

Pavel A. Gurikov, Mansi Aliveli, Preethi Aranala Gurumoorthi, Irina Smirnova
Scientific Reports
Cellular Automata and Applications
article

A cellular automata framework to study the diffusion in single and binary solvent systems

Pavel A. Gurikov, Mansi Aliveli, Preethi Aranala Gurumoorthi, Irina Smirnova
article en

Abstract

Abstract In this work, we present a two-dimensional cellular automata (CA) model to study mass transfer by diffusion of molecules in single and binary solvent systems. The method builds on Vanag’s probabilistic cellular automata (PCA), where diffusion is simulated through stochastic exchange of molecules between neighboring cells. While the original PCA framework effectively models single component diffusion driven by concentration gradients, it could not account for variable diffusion coefficients. We address this limitation by generalizing the PCA approach to handle binary systems, enabling the simulation of diffusion in heterogeneous materials with varied transport properties. This extension broadens the applicability of CA-based methods for capturing complex diffusion dynamics.

Scientific Reports
Openalex Percentile: Top 11%
Cellular Automata and Applications
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