Modeling the Impact of Grain Size on Corrosion Behavior of Ni-Based Alloys in Molten Chloride Salt via Cellular Automata

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper "Modeling the Impact of Grain Size on Corrosion Behavior of Ni-based Alloys in Molten Chloride Salt via Cellular Automata" presents a novel and insightful approach to understanding the corrosion dynamics of Ni-based alloys in high-temperature environments. Utilizing a cellular automata (CA) model, the authors innovatively combine the effects of grain size with corrosion processes, an area not extensively explored before. The methodology is robust, incorporating both diffusion and reaction models, and the CA simulations are validated against empirical data, ensuring scientific rigor. The study's relevance to materials science, particularly in the context of concentrated solar power (CSP) systems, underscores its practical significance.

However, several areas could benefit from further refinement. The reliance on literature values for parameter estimation suggests the need for experimental calibration to enhance accuracy. The model's simplification, focusing on a limited set of elements and reactions, and its two-dimensional limitation, somewhat constrain its comprehensiveness and real-world applicability. Additionally, the absence of an associative time scale and the complexity of the user interface are notable drawbacks. Despite these points, the study significantly advances our understanding of corrosion behavior in Ni-based alloys, demonstrating the potential of CA models in predicting and mitigating material degradation under extreme conditions. Addressing these limitations could further elevate the model's utility and impact.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Interesting approach to assess from a simulation view point the corrosion behavior as a function of composition and grain size of Ni-based alloys. It deserves to be published after some minor questions are clarified:

1) In Figure 1b and 1c displaying the number of Cl2 and O2 using the same colors can be confusing. The authors should correlate in a clearer the sequence of the corrosion processes giving rise to Cl2 and O2 and clarify their concentrations (are they the same?)

2)  The Voronoi diagram generator used should be better specified/included as supporting information indicating the programming language used

3) Explicit expressions for gibbs free energy and reactions rates should be added and explained more in detail

4) The multilayer model to calculate the thickness model should be briefly explained and not merely referred to. How is the original thickness (of the oxides i assume) calculated? The authors report thickness loss of 250 nm values. Are these consistent with experimental observations? 

5) The authors should provide experimental evidence reported in the literature matching their approach as regards thickness change dependence on grain boundary size

6) As perspective, it would be interesting if their approach can address grain sizea and surface roughness impact on corrosion inhibition when using inhibitors. A recent experimental work has clearly demonstrated the different mechanisms involved in corrosion inhibition when using the same alloy but different surface morphology and roughness. See S. Neupane et al., A model study on controlling dealloying corrosion attack by lateral modification of surfactant inhibitors, npj Materials Degradation 5 (2021) 29.

Author Response

Please see attachment

Author Response File: Author Response.pdf