Related papers: Identifying interatomic potentials for the accurat…
Nanocrystalline metal alloys show great potential as structural materials, but are often only available in small volumes such as thin films or powders. However, recent research has suggested that dopant segregation and grain boundary…
We derive interatomic potentials for zinc blende InAs, InP, GaAs and GaP semiconductors with possible applications in the realm of nanostructures. The potentials include bond stretching interaction between the nearest and next-nearest…
We construct a fast, transferable, general purpose, machine-learning interatomic potential suitable for large-scale simulations of $N_2$. The potential is trained only on high quality quantum chemical molecule-molecule interactions, no…
We present the results of a self-consistent, unified molecular dynamics study of simple model heteropolymers in the continuum with emphasis on folding, sequence design and the determination of the interaction parameters of the effective…
Acid solutions exhibit a variety of complex structural and dynamical features arising from the presence of multiple interacting reactive proton defects and counterions. However, disentangling the transient structural motifs of proton…
Machine-learned interatomic potentials enable realistic finite temperature calculations of complex materials properties with first-principles accuracy. It is not yet clear, however, how accurately they describe anharmonic properties, which…
A number of electronic devices involve metal/oxide interfaces in their structure where the oxide layer plays the role of electrical insulator. As the downscaling of devices continues, the oxide thickness can spread over only a few atomic…
Stabilization of grain structure is important for nanocrystalline alloys, and grain boundary segregation is a common approach to restrict coarsening. Doping can alter grain boundary structure, with high temperature states such as amorphous…
Chemical transformations, such as ion exchange, are commonly employed to modify nanocrystal compositions. Yet the mechanisms of these transformations, which often operate far from equilibrium and entail mixing diverse chemical species,…
Polymer-derived ceramics combine the thermal stability of ceramics with the versatile properties of carbon domains, but modeling their atomic-scale evolution during processing remains elusive due to the limitations of traditional…
We introduce a model to study the collisions of two ultracold diatomic molecules in one dimension interacting via pairwise potentials. We present results for this system, and argue that it offers lessons for real molecular collisions in…
Quadratic trapping potentials are widely used to experimentally probe biopolymers and molecular machines and drive transitions in steered molecular-dynamics simulations. Approximating energy landscapes as locally quadratic, we design…
Accounting for nuclear quantum effects (NQEs) can significantly alter material properties at finite temperatures. Atomic modeling using the path-integral molecular dynamics (PIMD) method can fully account for such effects, but requires…
To enable accurate molecular dynamics simulations of iron-chromium alloys with surfaces, we develop, based on density-functional-theory (DFT) calculations, a new interatomic Fe-Cr potential in the Tersoff formalism. Contrary to previous…
In this paper I propose a new model for representing the formation energies of multicomponent crystalline alloys as a function of atom types. In the cases when displacements of atoms from their equilibrium positions are not large, the…
While molecular dynamics (MD) is a very useful computational method for atomistic simulations, modeling the interatomic interactions for reliable MD simulations of real materials has been a long-standing challenge. In 2007, Behler and…
Magnetic complex-oxide heterostructures are of keen interest because a wealth of phenomena at the interface of dissimilar materials can give rise to fundamentally new physics and potentially valuable functionalities. Altered magnetization,…
Machine learning (ML) based interatomic potentials are emerging tools for materials simulations but require a trade-off between accuracy and speed. Here we show how one can use one ML potential model to train another: we use an existing,…
Recently, we developed a method to construct polynomial interatomic potentials from ab-initio calculations in order to accurately describe laser excited solids [PRL 124, 085501 (2020)]. However, ab-initio methods, and therefore analytical…
The atomic distribution in amorphous FeZr alloys is found to be close to random, nevertheless, the composition can not be viewed as being homogenous at the nm-scale. The spatial variation of the local composition is identified as the root…