Related papers: Solid-Liquid Phase Diagrams for Binary Metallic Al…
The equilibrium phase diagram of a 1:1 symmetrical mixture composed of oppositely charged colloids is calculated using Monte Carlo simulations. We model the system by the DLVO effective interaction potential. The phase diagram is similar to…
The study of alloys using computational methods has been a difficult task due to the usually unknown stoichiometry and local atomic ordering of the different structures experimentally. In order to combat this, first-principles methods have…
We develop and compare four interatomic potentials for iron: a simple machine-learned embedded atom method (EAM) potential, a potential with machine-learned two- and three-body-dependent terms, a potential with machine-learned EAM and…
Compared to pure fluids, binary mixtures display a very diverse phase behavior, which depends sensitively on the parameters of the microscopic potential. Here we investigate the phase diagrams of simple model mixtures by use of a…
An interatomic potential (termed EAM-21) has been developed with the embedded atomic method (EAM) for CrFeMnNi quaternary HEAs. This potential is based on a previously developed potential for CrFeNi ternary alloys. The parameters to develop…
The suitability of a range of interatomic potentials for elemental tin was evaluated in order to identify an appropriate potential for modeling the stanene (2D tin) allotropes. Structural and mechanical properties of the flat (F),…
In the context of the modified Becke-Johnson (mBJ) potential, we recently underlined that $\bar{g}$, the average of $\left\vert\nabla\rho\right\vert/\rho$ in the unit cell, has markedly different values in transition-metal oxides and pure…
In this paper we devise and analyze a mixed finite element method for a modified Cahn-Hilliard equation coupled with a non-steady Darcy-Stokes flow that models phase separation and coupled fluid flow in immiscible binary fluids and diblock…
A self-consistent model for the simulation of Ge-rich Ge$_2$Sb$_2$Te$_5$ phase change memories is presented. Combining the multi-phase field model and a phase-aware electro-thermal solver, it reproduces the multi-physics behavior of the…
We describe a first-principles statistical mechanics method to calculate the free energies of crystalline alloys that depend on temperature, composition, and strain. The approach relies on an extension of the alloy cluster expansion to…
A machine-learned interatomic potential for Ge-rich Ge$_x$Te alloys has been developed aiming at uncovering the kinetics of phase separation and crystallization in these materials. The results are of interest for the operation of embedded…
The accurate prediction of phase diagrams is of central importance for both the fundamental understanding of materials as well as for technological applications in material sciences. However, the computational prediction of the relative…
For the first time, the combination of experimental preparation and results of fully atomistic simulations of an oligoelectrolyte multilayer (OEM) made of poly(diallyl dimethyl ammonium chloride)/poly(styrene sulfonate sodium salt)…
NpT ensemble Monte Carlo simulations were performed for fully flexible Lennard-Jones chains in the solid phase. The bond length between monomers within the chains is fixed to $L=\sigma$ and the molecule is free to adopt any configuration.…
Modern compound prediction methods can efficiently screen large numbers of crystal structure phases and direct the experimental search for new materials. One of the most challenging problems in alloy theory is the identification of stable…
The design of next generation \beta-type titanium implants requires detailed knowledge of the relevant stable and metastable phases at temperatures where metallurgical heat treatments can be performed. Recently, a standard specification for…
We develop an approach to apply Wang-Landau algorithm to multicomponent alloys in semi-grand-canonical ensemble. Although the Wang-Landau algorithm has great advantages over conventional sampling methods, there are few applications to…
A theoretical model of shape-anisometric particles embedded in a cubic lattice is formulated for binary mixtures combining rod-like, plate-like and spherical particles. The model aims at providing a tool for the prediction and…
Quantum Monte Carlo and quantum chemistry techniques are used to investigate pseudopotential models of the lithium hydride (LiH) molecule. Interatomic potentials are calculated and tested by comparing with the experimental spectroscopic…
Machine learning interatomic potentials (MLIPs) have become a workhorse of modern atomistic simulations, and recently published universal MLIPs, pre-trained on large datasets, have demonstrated remarkable accuracy and generalizability.…