Chemical short range order, Voronoi

[nana8]

Dear OVITO support team,

I am currently studying a high-entropy alloy system and would like to quantify the chemical short-range order (CSRO) by analyzing atomic pair statistics. Specifically, I want to use the Voronoi analysis module in OVITO to count the nearest-neighbor occurrences for various atomic pair types, including both unlike pairs (e.g., A-B, A-C, A-D, B-C) and like pairs (e.g., A-A). Is this achievable with the Voronoi analysis tool? If not, could you suggest alternative modules or workflows within OVITO to accomplish this goal?

Thank you very much for your guidance.

[utt]

It depends a bit on what you’re trying to do.

• You can use the Voronoi modifier with the “Neighbor bonds” option to create bonds between neighbors, and then use either a custom Python modifier or the Bond length distribution modifier to aggregate the bond data.
• Alternatively, you can use the Radial distribution function (RDF) modifier with the “Partial RDFs per particle type” setting to count neighbors within a given distance of a central particle. Again, depending on your needs a custom Python modifier might be necessary for data aggregation.
• If you want an out-of-the-box solution, you can install the Warren-Cowley short-range order parameters OVITO extension and compute short-range order parameters directly from the Pro GUI or in a scripting context.