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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Ori, Guido
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (7/7 displayed)
- 2024Enhanced Structural Description of Sodium Vanadium Phosphate Glasses: A Combined Experimental and Molecular Dynamics Study
- 2020Chalcogenide glasses for innovation in applied science: fundamental issues and new insightscitations
- 2019Chalcogenide glasses as a playground for the application of first-principles molecular dynamics to disordered materialscitations
- 2019Chalcogenide glasses as a playground for the application of first-principles molecular dynamics to disordered materialscitations
- 2018The role of dispersion forces on the atomic structure of glassy chalcogenides: The case of GeSe4 and GeS4citations
- 2018The role of dispersion forces on the atomic structure of glassy chalcogenides: The case of GeSe4 and GeS4citations
- 2015Comparison of precipitated calcium carbonate/polylactic acid and halloysite/polylactic acid nanocompositescitations
Places of action
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article
Chalcogenide glasses as a playground for the application of first-principles molecular dynamics to disordered materials
Abstract
An overview of the major first-principles methods used to simulate condensed phases is presented, with special emphasis on chalcogenide glasses. The scope of this review article is to offer a survey of fundamental algorithms and techniques, accompanied by a few recent examples particularly representative of computational materials science applied to disordered chalcogenide phases. Special attention is devoted to the inclusion of long-range van der Waals dispersion forces, treatment of the exact exchange, dynamical simulations and extraction of optical and dielectric properties. Machine learning techniques are introduced as recent forefront applications of first-principle methods. In this latter case, accurate quantum-mechanics based simulations are crucial to generate a data base exploited by neuronal-network type algorithms to create accurate interatomic potentials (force fields) allowing for large and long-lasting simulations of realistic disordered materials. The atomic-level knowledge provided by the combination of high-performance computing and advanced computational methods pave the route for a rational approach to the design of novel chalcogenides possessing tuned properties for specific applications in next-generation devices.