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Percolation Diagrams Derived from First-Principles Investigation of Chemical Short-Range Order in Binary Alloys

Abhinav Roy, Karl Sieradzki, Michael J. Waters, James M. Rondinelli, Ian D. McCue

Abstract

Recent developments in the percolation theory of passivation have shown that chemical short-range order (SRO) affects the aqueous passivation behavior of alloys. However, there has been no systematic exploration to quantify these SRO effects on percolation in practical alloys and the related passivation behavior. In this study, we quantify the effects of SRO on percolation in a binary size-mismatched Cu-Rh alloy and study the related passivation behavior. We develop a mixed-space cluster expansion model trained on the mixing energy calculated using density functional theory. We use the cluster expansion model to sample the configuration space via variance-constrained semi-grand canonical Monte Carlo simulations and develop SRO diagrams over a range of compositions and temperatures. Building on this with the percolation crossover model, specifically the variation of percolation threshold with SRO in the FCC lattice, we construct the first nearest-neighbor chemical percolation diagram. These diagrams can inform the design of the next generation of corrosion-resistant metallic alloys.

Percolation Diagrams Derived from First-Principles Investigation of Chemical Short-Range Order in Binary Alloys

Abstract

Recent developments in the percolation theory of passivation have shown that chemical short-range order (SRO) affects the aqueous passivation behavior of alloys. However, there has been no systematic exploration to quantify these SRO effects on percolation in practical alloys and the related passivation behavior. In this study, we quantify the effects of SRO on percolation in a binary size-mismatched Cu-Rh alloy and study the related passivation behavior. We develop a mixed-space cluster expansion model trained on the mixing energy calculated using density functional theory. We use the cluster expansion model to sample the configuration space via variance-constrained semi-grand canonical Monte Carlo simulations and develop SRO diagrams over a range of compositions and temperatures. Building on this with the percolation crossover model, specifically the variation of percolation threshold with SRO in the FCC lattice, we construct the first nearest-neighbor chemical percolation diagram. These diagrams can inform the design of the next generation of corrosion-resistant metallic alloys.

Paper Structure

This paper contains 4 sections, 3 equations, 3 figures.

Table of Contents

  1. CRediT authorship contribution statement
  2. Declaration of competing interest
  3. Acknowledgments
  4. Supplementary materials

Figures (3)

  • Figure 1: (a) Helmholtz free energy obtained via thermodynamic integration. (b) Comparison of the computed and experimental chakrabarti1982cu Cu-Rh binary phase diagram.
  • Figure 2: SRO diagrams for (left) first, (center) second, and (right) third nearest-neighbor Warren-Cowley $\alpha$ parameters. The computed binodal is overlaid on the SRO diagrams to delineate the single-phase solid solution region (highlighted by the red box).
  • Figure 3: Chemical percolation diagram (CPD) for the Cu-Rh alloy. (a) The percolation threshold diagram of CPD obtained from the polynomial fit. (b) The percolation threshold difference diagram. The region within the composition range of $0.175\leq c_{\mathrm{Rh}}\leq0.21$, represented by the dashed lines, delineates the range of maximum possible variation in $p_{c}^{3D}(\alpha_1)$ based on the values of $\alpha_1$ used for the MC-RNG analysis (Figure S14 of SM).