I am designing a ternary HCP alloy with a highly skewed composition: A-90%, B-6%, C-4%. For SQS generation key challenges are:
Minority Element Placement: Elements B (6%) and C (4%) are sparsely distributed. How can we ensure their random placement (e.g., avoiding B-B/C-C clustering) while enforcing pairwise probabilities (e.g., A-B: 10.8%, A-C: 7.2%)?
Dominance of A-A Correlations: A-A pairs dominate (81% probability). How do we prioritize A-A correlation accuracy while resolving minority contributions without introducing artificial periodicity?
HCP Lattice Constraints: How should correlation shells (e.g., 1st/2nd neighbors in HCP) be prioritized to minimize periodicity errors?
Request for Guidance:
What strategies, workflows:
Adjusting Monte Carlo parameters (e.g., temperature, swap rules) for sparse B/C placement.
Validating beyond pair correlations (e.g., triplet terms).
Addressing HCP symmetry challenges (e.g., supercell anisotropy).
Any insights or references to ternary SQS work with skewed compositions would be invaluable!