Related papers: Transferable potential for molecular dynamics simu…
Borosilicate glasses are traditionally challenging to model using atomic scale simulations due to the composition and thermal history dependence of the coordination state of B atoms. Here, we report a new empirical interatomic potential…
The accuracy of molecular simulations is fundamentally limited by the interatomic potentials that govern atomic interactions. Traditional potential development, which relies heavily on ab initio calculations, frequently struggles to…
We adapt and apply a recently developed optimization scheme used to obtain effective potentials for aluminosilicate glasses to include the network former boron into the interaction parameter set. As input data for the optimization, we used…
We reproduced the simulations described in Wang et al [J. Non-Cryst. Sol., 498 (2018) 294-304] and found we could not obtain the results reported. The root cause was identified to be incorrect atom masses in the original simulation files.…
We apply a recently developed optimization scheme to obtain effective potentials for alkali and alkaline-earth aluminosilicate glasses that contains lithium, sodium, potassium, or calcium as modifiers. As input data for the optimization, we…
We study a calcium aluminosilicate glass of composition (SiO2)0.60(Al2O3)0.10(CaO)0.30 by means of molecular dynamics. To this end, we conduct parallel simulations, following a consistent methodology, but using three different potentials.…
Lithium borosilicate (LBS) glass is a prototypical lithium-ion conducting oxide glasses available for an all-solid state buttery. Nevertheless, the atomistic modeling of LBS glass using $ab$ $initio$ (AIMD) and classical molecular dynamics…
We develop a transferable machine learning model which predicts structural relaxation from amorphous supercooled liquid structures. The trained networks are able to predict dynamic heterogeneity across a broad range of temperatures and time…
The central approximation made in classical molecular dynamics simulation of materials is the interatomic potential used to calculate the forces on the atoms. Great effort and ingenuity is required to construct viable functional forms and…
The development by machine learning of models predicting materials' properties usually requires the use of a large number of consistent data for training. However, quality experimental datasets are not always available or self-consistent.…
We propose a new scheme to parameterize effective potentials that can be used to simulate atomic systems such as oxide glasses. As input data for the optimization, we use the radial distribution functions of the liquid and the vibrational…
An analytical framework is proposed to describe the elasticity, viscosity and fragility of metallic glasses in relation to their atomic-level structure and the effective interatomic interaction. The bottom-up approach starts with forming an…
Using a realistic flexible molecule model of the fragile glass former orthoterphenyl, we calculate via molecular dynamics simulation the collective dynamic structure factor, recently measured in this system by Inelastic X-ray Scattering.…
We compare the ability of various interaction potentials to predict the structural and mechanical properties of silica and sodium silicate glasses. While most structural quantities show a relatively mild dependence on the potential used,…
With the advent of powerful computer simulation techniques, it is time to move from the widely used knowledge-guided empirical methods to approaches driven by data science, mainly machine learning algorithms. We investigated the predictive…
We use ab initio simulations to study the static and dynamic properties of a sodium borosilicate liquid with composition 3Na_2O-B_2O_3-6SiO_2, i.e. a system that is the basis of many glass-forming materials. In particular we focus on the…
First-principles based modeling on phonon dynamics and transport using density functional theory and Boltzmann transport equation has proven powerful in predicting thermal conductivity of crystalline materials, but it remains unfeasible for…
The individual optimization of quantum circuit parameters is currently one of the main practical bottlenecks in variational quantum eigensolvers for electronic systems. To this end, several machine learning approaches have been proposed to…
Molecular dynamics simulations are an important tool for describing the evolution of a chemical system with time. However, these simulations are inherently held back either by the prohibitive cost of accurate electronic structure theory…
Modeling inorganic glasses requires an accurate representation of interatomic interactions, large system sizes to allow for intermediate-range structural order, and slow quenching rates to eliminate kinetically trapped structural motifs.…