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A Monte Carlo method is used in order to simulate the competition between the molecular relaxation and crystallization times in the formation of a glass. The results show that nucleation is avoided during supercooling and produce…

Disordered Systems and Neural Networks · Physics 2009-11-07 Adrian Huerta , Gerardo G. Naumis

Structurally and chemically complex materials such as amorphous metallosilicates underpin major catalytic and separation technologies, yet their intrinsic complexity challenges reliable atomistic modeling under realistic conditions.…

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or…

Computational Physics · Physics 2021-05-14 Vincent Dufour-Décieux , Rodrigo Freitas , Evan J. Reed

Atom density profile arising in the atomic beam after passing through the one or two microfabricated structures (MS) is considered. Two limiting cases the beam with large and small angular divergence are considered. An equivalence of the…

Atomic Physics · Physics 2007-05-23 B. Dubetsky , P. R. Berman

The atomistic mechanisms occurring during the processes of aging and rejuvenation in glassy materials involve very small structural rearrangements that are extremely difficult to capture experimentally. Here we use in-situ X-ray diffraction…

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.…

Disordered Systems and Neural Networks · Physics 2015-06-19 M. Bauchy

A fundamental objective of materials modeling is identifying atomic structures that align with experimental observables. Conventional approaches for disordered materials involve sampling from thermodynamic ensembles and hoping for an…

Materials Science · Physics 2025-09-30 Tigany Zarrouk , Miguel A. Caro

A major challenge in simulating glassy systems is the ability to generate configurations that may be found in equilibrium at sufficiently low temperatures, in order to probe static and dynamic behaviour close to the glass transition. A…

Soft Condensed Matter · Physics 2024-06-19 Pallabi Das , Anshul D. S. Parmar , Srikanth Sastry

The first version of the machine learning greybox model i-Melt was trained to predict latent and observed properties of K$_2$O-Na$_2$O-Al$_2$O$_3$-SiO$_2$ melts and glasses. Here, we extend the model compositional range, which now allows…

Materials Science · Physics 2023-07-11 Charles Le Losq , Barbara Baldoni

An empirical potential that has been widely used to perform molecular dynamics studies on the fracture behavior of FeP metallic glasses is shown to exhibit spinodal decomposition in the composition range commonly studied. The phosphorous…

Materials Science · Physics 2019-01-30 Yezeng He , Peng Yi , Michael L. Falk

Molecular dynamics simulations at a constant electric potential are an essential tool to study electrochemical processes, providing microscopic information on the structural, thermodynamic, and dynamical properties. Despite the numerous…

While the structural dynamics of chromophores are of interest for a range of applications, it is experimentally very challenging to resolve the underlying microscopic mechanisms. Glassy dynamics are also challenging for atomistic…

Materials Science · Physics 2025-09-03 Eric Lindgren , Jan Swensson , Christian Müller , Paul Erhart

Electron tomography is a technique used in both materials science and structural biology to image features well below optical resolution limit. In this work, we present a new algorithm for reconstructing the three-dimensional(3D)…

Signal Processing · Electrical Eng. & Systems 2018-07-12 David Ren , Michael Chen , Laura Waller , Colin Ophus

Background: Semiconductor-doped glasses are treated actively through many years and continue to be of great interest because challenged features of nanosized semiconductors of various chemical nature. Copper chalcogenides have discovered…

Mesoscale and Nanoscale Physics · Physics 2022-11-28 Valerij S. Gurin , Alexander A. Alexeenko

Atomic force microscopy (AFM) is a well-known tool for studying surface roughness and to collect depth information about features on the top atomic layer of samples. By combining secondary ion mass spectroscopy (SIMS) with focused ion beam…

Materials Science · Physics 2022-10-18 Lex Pillatsch , Szilvia Kalácska , Xavier Maeder , Johann Michler

Two different preparation methods (liquid-quenching and evaporation) of chalcogenide glasses have been investigated by molecular dynamics simulations. Our particular aim was to determine how the structural changes occur due to the different…

Disordered Systems and Neural Networks · Physics 2016-08-31 J. Hegedus , K. Kohary , S. Kugler

Atomic force microscopy (AFM) is one of the most promising methods for investigating the structure of materials at the micro and nanoscale levels, as well as their local physical-mechanical properties. The experimental data obtained with…

Materials Science · Physics 2018-05-07 Oleg K. Garishin , Roman I. Izyumov , Alexander L. Svistkov

A new method is presented to generate atomic structures that reproduce the essential characteristics of arbitrary material systems, phases, or ensembles. Previous methods allow one to reproduce the essential characteristics (e.g. chemical…

Materials Science · Physics 2024-09-24 James M. Goff , Coreen Mullen , Shizhong Yang , Oleg N. Starovoytov , Mitchell A. Wood

Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with…

The development of new manufacturing techniques such as 3D printing have enabled the creation of previously infeasible chemical reactor designs. Systematically optimizing the highly parameterized geometries involved in these new classes of…

Computational Engineering, Finance, and Science · Computer Science 2023-07-10 Tom Savage , Nausheen Basha , Jonathan McDonough , Omar K Matar , Ehecatl Antonio del Rio Chanona
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