| 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
Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulation
Abstract
Load transfer of the graphene/carbon nanotube (CNT)/polyethylene hybrid nanocomposite is studied here from molecular dynamics (MD) simulations. Simulations of this composite material under uniaxial tension were conducted by varying CNT’s position and diameter in the polymer matrix. The obtained results show that: (1) The peak strength of stress and strain evolution in the polymer matrix is lower than the peak strength of the graphene/graphene and graphene/polymer interfaces. Hence, the damage zone is always located in the polymer matrix. (2) Agglomerated two-layer graphenes do not possess an increased value in the peak strength compared with single-layer graphene-reinforced polymer nanocomposite (PNC), while two separate layers of graphene show slightly higher peak strength. (3) The largest peak strength is observed before CNT moves to the center of the polymer matrix. The damage location moves from the upper to the lower part of CNT when the CNT is located at the centre of polymer matrix. (4) The influence of the CNT diameter on the peak strength is not obvious, while the damage location and shape in the polymer matrix changes with respect to varying CNT diameters. In addition, the damage zone always falls outside the interphase zone.