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This article presents a statistical approach for atomistic calculations of vacancy formation energy, which is expected to exhibit a probability distribution in concentrated solid-solution alloys, due to the variation in atomic environment. Demonstrated using a random FeCrNi ternary alloy, a general formulation is given for applications in random, concentrated alloys with any number of components. The proposed approach calculates the mean vacancy formation energy, based on the total energies of the reference and defected supercells—each with a vacancy—without separate calculations for chemical potentials, thus avoiding the additional computational cost and the associated uncertainty. The chemical potential of each component can be back-derived in a self-consistent manner to give the distribution of vacancy formation energy. This is opposed to most current studies, in which the individual chemical potentials are calculated separately prior to calculating the vacancy formation energy. It is also found that, with the same mean vacancy formation energy, a broader distribution may lead to a higher equilibrium vacancy concentration at a given temperature, indicating the critical importance of statistically obtaining the full distribution of vacancy formation energy.

The influence of Cu precipitation on the tensile properties of Fe–1.1% Cu–0.9% Ni ternary alloy at different temperatures are analyzed using molecular dynamics (MD) method. The local lattice structural transition around Cu-rich clusters is generated by Cu-rich clusters forming during continuous cooling process. The formation of Cu-rich clusters and matrix of local lattice structural transition result in the decrease of tensile yield strength of the matrix material at room temperature. Therefore, the matrix becomes brittle and tends to fracture in the local structural transition area. It has been found that the formation of Cu-rich clusters reduces the yield strength of the matrix more greatly at aging temperature than room temperature. Furthermore, the higher the temperature is, the greater the degree is. Cu-rich clusters play a significant role in strengthening material at early stage, while the material strength decreases with time increase.

We present a study of the short- and long- range ordering phenomena that take place in the bcc β phase of the ternary alloy Cu–Zn–Al. The results have been obtained by means of Monte Carlo simulations based on a three states Ising Hamiltonian. The evolution of the long- and short-range order degrees, internal energy, entropy and Helmholtz free energy are calculated as functions of temperature. The impact of short range order on the thermodynamics of the system is evaluated. The results obtained with the Monte Carlo technique are contrasted with those obtained within two different analytical approximations, whose validity is discussed. The calculated thermal variation of the specific heat near the long range ordering transitions is discussed and compared with experimental data.

A computer model based on radial base function artificial neural network (RBFANN) was designed for the simulation and prediction of undercooled liquid region Δ T x of glass forming alloys. The model was trained using data from the published literature as well as own experimental data. The performance of RBFANN model is examined by the predicted and simulated results of the influence of kinds of alloys and elements, large and minor change of element content on the reduced glass transition temperature, and composition dependence of Δ T x for La–Al–Ni ternary alloy system. The results show that the RBFANN model is reliable and adequately. Moreover, a group of new Zr–Al–Ni–Cu bulk metallic glasses is designed by RBFANN model. Their predicted Δ T x s are in agreement with the corresponding experimental values.

A combination of X-ray and neutron powder diffraction has been used to measure the two long range order parameters vs. temperature below the disorder-B2 transition in the ternary alloy Cu 2 AlMn. The results indicate that at temperatures just below the critical point the Al + Mn sublattice is enriched in Al. First-principles calculations based on only the atomic numbers of Cu, Mn and Al support the experimentally-observed preference of Al for the Al + Mn sublattice, and reveal the interplay between the constituent binary systems that gives rise to this behavior.

The empirical pseudopotential method coupled with the virtual crystal approximation is used to compute the electronic conduction band-edge charge densities at the Γ and X points for the ternary alloy Cd x Zn 1−x S. We find that these charge densities are strongly dependent upon the stochiometric coefficient x . Such differences are crucial for a comprehensive understanding of interstitial impurities and the response of specific band states to perturbation in ternary alloy semiconductors.