| People | Locations | Statistics |
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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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Zhuang, Xiaoying
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (15/15 displayed)
- 2024Investigation of crack segmentation and fast evaluation of crack propagation, based on deep learningcitations
- 2021An efficient optimization approach for designing machine learning models based on genetic algorithm
- 2019Computational Machine Learning Representation for the Flexoelectricity Effect in Truncated Pyramid Structures
- 2019Two-Dimensional SiP, SiAs, GeP and GeAs as Promising Candidates for Photocatalytic Applicationscitations
- 2019Theoretical realization of two-dimensional M 3 (C 6 X 6 ) 2 (M = Co, Cr, Cu, Fe, Mn, Ni, Pd, Rh and X = O, S, Se) metal–organic frameworkscitations
- 2018Fracture Properties of Graphene-Coated Silicon for Photovoltaicscitations
- 2017Uncertainties propagation in metamodel-based probabilistic optimization of CNT/polymer composite structure using stochastic multi-scale modeling
- 2017A unified framework for stochastic predictions of Young's modulus of clay/epoxy nanocomposites (PCNs)
- 2017Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters
- 2017Stochastic predictions of interfacial characteristic of polymeric nanocomposites (PNCs)
- 2017Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulation
- 2014Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulations
- 2014Optimization of fiber distribution in fiber reinforced composite by using NURBS functions
- 2014Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulationcitations
- 2014Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulationcitations
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article
Theoretical realization of two-dimensional M 3 (C 6 X 6 ) 2 (M = Co, Cr, Cu, Fe, Mn, Ni, Pd, Rh and X = O, S, Se) metal–organic frameworks
Abstract
<p>Two-dimensional (2D) conductive metal–organic framework (MOF) lattices have recently gained remarkable attentions because of their outstanding application prospects. Most recently, Cu-hexahydroxybenzene MOF was for the time experimentally realized, through a kinetically controlled approach. Cu-HHB belongs to the family of conductive MOFs with a chemical formula of M<sub>3</sub>(C<sub>6</sub>X<sub>6</sub>)<sub>2</sub>(X = NH, O, S). Motivated by the recent experimental advance in the fabrication of Cu-HHB, we conducted extensive first-principles simulations to explore the thermal stability, mechanical properties and electronic characteristics of M<sub>3</sub>(C<sub>6</sub>X<sub>6</sub>)<sub>2</sub>(M = Co, Cr, Cu, Fe, Mn, Ni, Pd, Rh and X = O, S, Se) monolayers. First-principles results confirm that all considered 2D porous lattices are thermally stable at high temperatures over 1500 K. It was moreover found that these novel 2D structures can exhibit linear elasticity with considerable tensile strengths, revealing their suitability for practical applications in nanodevices. Depending on the metal and chalcogen atoms in M<sub>3</sub>(C<sub>6</sub>X<sub>6</sub>)<sub>2</sub>monolayers, they can yield various electronic and magnetic properties, such as; magnetic semiconducting, perfect half metallic, magnetic and nonmagnetic metallic behaviors. This work highlights the outstanding physics of M<sub>3</sub>(C<sub>6</sub>X<sub>6</sub>)<sub>2</sub>2D porous lattices and will hopefully help to expand this conductive MOF family, as promising candidates to design advanced energy storage/conversion, electronics and spintronics systems.</p>