Magnetochemical effects on phase stability and vacancy formation in fcc Fe-Ni alloys

Efficient first principles based modeling via machine learning: from simple representations to high entropy materials

“…Therefore, ML models trained with unrelaxed structures only learn from the atomic conguration in a way similar to on-lattice models. 29,[65][66][67]…”

“…When building physics-based model Hamiltonians, a common practice is to use a bottom-up approach, where one rst ts the two-body interaction parameters with low-order systems, and gradually adds more model parameters by including higher-order interactions for more complex systems. 67 This is oen considered to be physically more reasonable than just performing a single t for all the model parameters once. The latter can be prone to overtting by inappropriately attributing more contribution to the higherorder interactions, whereas the bottom-up approach provides a way to add regularization to higher-order interactions.…”

Semi-supervised generative approach to chemical disorder: application to point-defect formation in uranium–plutonium mixed oxides

“…The BSD formation energy in concentrated disordered compounds can be calculated as: 35,36 E f BSD ( x c ) = E BSD ( x c ) − E ( x c ) + μ c + 2 μ O − k B T log( y c ),where c can be either U or Pu, μ is the chemical potential of U, Pu, or O, and y c is the concentration of species c in the supercell, so y U = 1 − y Pu . E ( x c ) is the energy of a supercell without defects, where the cation vacancy has been replaced by a cation of type c. E BSD ( x c ) is the energy of the same supercell with the cation c and two oxygen atoms removed.…”

Unconventional Nonequilibrium Phase Stabilization in FeNi Alloy Examined by Positron Annihilation Spectroscopy

“…[19][20][21][22] Mentes et al [23] employed spectroscopic photoemission and low-energy electron Microscopy (SPLEEM) to study the in situ deposition of bcc FeNi film and reported that the fcc/bcc phase separation was mediated by vacancies on annealing above 583 K. More recently, Jacob et al [24] obtained a stable α-FeNi up to 36 at% Ni through low-temperature solution-based reduction method employing polyols. Since the vacancy formation energy ðE vac Þ is inversely related to the temperature [25,26] a low vacancy concentration is expected in chemically synthesized samples. In such a scenario, the reason for the stability of the bcc phase could be understood only if the role of the defects is understood.…”

“…Since the vacancy formation energy is inversely related to the temperature [ 25,26 ] a low vacancy concentration is expected in chemically synthesized samples. In such a scenario, the reason for the stability of the bcc phase could be understood only if the role of the defects is understood.…”