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Atomistic simulation of densified amorphous alumina
(SOCIEDAD MEXICANA DE FISICA, 2002)
On the determination of defect dipoles from atomistic simulations using periodic boundary conditions
(Taylor & Francis Ltd, 2016-11)
By solving the problem of a periodic distribution of point defects in general anisotropic media, we give an alternative, more direct proof, of the relatively recent procedure that extracts dipole tensors from the stress ...
Atomistic modeling of dislocations in a random quinary high-entropy alloy
(Elsevier, 2020-02)
The structure and mobility of dissociated ½〈1 1 0〉 dislocations in a model FCC high entropy alloy is studied using atomistic simulations. The simulations are performed using model embedded atom method (EAM) potentials for ...
FoamExplorer: Automated measurement of ligaments and voids for atomistic systems
(Elsevier, 2020-12)
Atomistic simulations are often used to explore the mechanical and chemical properties of a variety of materials and structures, such as nanowires, whiskers, nanospheres, nanotrusses, and nanoscale foams, among others. ...
Aplicação do jogo ludo atomística no ensino de química
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação de Mestrado Profissional em Química - PPGQCâmpus São Carlos, 2015-12-17)
This work presents an experience directed on the construction, development and implementation of a playful activity in the Teaching of Chemistry, with students of the first year of high school State School "Captain Agenor ...
FoamExplorer: Automated measurement of ligaments and voids for atomistic systems
(Elsevier, 2020-12)
Atomistic simulations are often used to explore the mechanical and chemical properties of a variety of materials and structures, such as nanowires, whiskers, nanospheres, nanotrusses, and nanoscale foams, among others. ...
Improved atomistic Monte Carlo models based on ab-initio -trained neural networks: Application to FeCu and FeCr alloys
(American Physical Society, 2017-06)
We significantly improve the physical models underlying atomistic Monte Carlo (MC) simulations, through the use of ab initio fitted high-dimensional neural network potentials (NNPs). In this way, we can incorporate energetics ...