Cellular automaton simulation of a simple corrosion mechanism: mesoscopic heterogeneity versus macroscopic homogeneity

Cellular Automata Modeling as a Tool in Corrosion Management

Cellular automata models have emerged as a valuable tool in corrosion management. This manuscript provides an overview of the application of cellular automata models in corrosion research, highlighting their benefits and contributions to understanding the complex nature of corrosion processes. Cellular automata models offer a computational approach to simulating corrosion behavior at the microscale, capturing the intricate interactions between electrochemical reactions, material properties, and environmental factors and generating a new vision of predictive maintenance. It reviews the key features of cellular automata, such as the grid-based representation of the material surface, the definition of state variables, and the rules governing cell-state transitions. The ability to model local interactions and emergent global behavior makes cellular automata particularly suitable for simulating corrosion processes. Finally, cellular automata models offer a powerful and versatile approach to studying corrosion processes, expanding models that can continue to enhance our understanding of corrosion and contribute to the development of effective corrosion prevention and control strategies.

Native diffusion of fluorogenic turn-on dyes accurately report interfacial chemical reaction locations

Single-molecule fluorescence microscopy with "turn-on" dyes that change fluorescent state after a reaction report on the chemistry of interfaces relevant to analytical and bioanalytical chemistry. Paramount to accurately understanding the phenomena at the ultimate detection limit of a single molecule is ensuring fluorophore properties such as diffusion do not obscure the chemical reaction of interest. Here, we develop Monte Carlo simulations of a dye that undergoes reduction to turn-on at the cathode of a corroded iron surface taking into account the diffusion of the dye molecules in a total internal reflection fluorescence (TIRF) excitation volume, location of the cathode, and chemical reactions. We find, somewhat counterintuitively, that a fast diffusion coefficient of D = 10⁸ nm²/s, corresponding to the dye in aqueous solution, accurately reports the location of single reaction sites. The dyes turn on and are present for the acquisition of a single frame allowing for localization before diffusing out of the thin TIRF excitation volume axially. Previously turned-on (i.e., activated) dyes can also randomly hit the surface surrounding the reaction site leading to a uniform increase in the background. Using concentrations that lead to high turnover rates at the reaction site can achieve signal-to-background ratios of  ~100 in our simulation. Therefore, the interplay between diffusion, turn-on reaction rate, and concentration of the dye must be strategically considered to produce accurate images of reaction locations. This work demonstrates that modeling can assist in the design of single-molecule microscopy experiments to understand interfaces related to analytical chemistry such as electrode, nanoparticle, and sensor surfaces.

Cellular Automata in Chemistry and Chemical Engineering

We review the modern state of cellular automata (CA) applications for solving practical problems in chemistry and chemical technology. We consider the problems of material structure modeling and prediction of materials' morphology-dependent properties. We review the use of the CA approach for modeling diffusion, crystallization, dissolution, erosion, corrosion, adsorption, and hydration processes. We also consider examples of hybrid CA-based models, which are combinations of various CA with other computational approaches and modeling methods. Finally, we discuss the use of high-performance parallel computing to increase the efficiency of CA.