Database-driven semigrand canonical Monte Carlo method: Application to segregation isotherm on defects in alloys.

The application of existing semigrand canonical ensemble Monte Carlo algorithms to alloys requires the chemical potential difference values between pairs of atomic species in the alloys as inputs. However, finding the appropriate values for a target system at a desired temperature and bulk composition is a time-consuming task consisting of multiple test runs to determine the chemical potential differences. This problem becomes more serious when dealing with systems containing three or more atomic species, such as medium- and high-entropy alloys, due to the increase of the number of chemical potential differences that need to be calculated.