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Multiscale study of influence of interfacial decohesion on piezoresistivity of graphene/polymer nanocomposites
28.05.2019


Dr. Fabrice Detrez, MSME Méca


Category: Séminaires de l'équipe CT


Lieu et heure:   Salle N20bis, bâtiment Lavoisier, 14h.

Intervenant: : Dr. Fabrice DETREZ

MSME  Equipe Méca

Résumé: 

Multiscale study of influence of interfacial decohesion on piezoresistivity of graphene/polymer nanocomposites


Fabrice Detrez



A multiscale strategy is proposed to study the role of interfacial decohesion on the piezoresistive properties of graphene/polymer nanocomposite [1]. A cohesive zone model is identified by atomistic simulations. This cohesive zone model enriches imperfect interfaces, which model graphene sheets, at mesoscale in our continuum mechanical model. This nonlinear mechanical model is used to generate deformed representative volume element to study influence of strain and interfacial decohesion on the conductivity of graphene/polymer nanocomposites. The effective conductivity is studied with an electric continuum model at mesoscale that incorporates the tunneling effect [2, 3, 4]. A conductor-insulator transition is observed for elongations above 2% for graphene volume fraction just above the percolation threshold. The transition appears for an elongation of 8% instead of 2%, when the interfacial decohesion is removed.


References

[1] Lu, X.,Detrez, F., Yvonnet, J., Bai, J.“Multiscale study of influence of interfacial decohesion on piezoresistivity of graphene/polymer nanocomposites”, Modelling Simul. Mater. Sci. Eng., 27, 035001 (2019).

[2] Lu, X., Yvonnet, J., Detrez, F., Bai, J., “Multiscale modeling of nonlinear electric conductivity in graphene-reinforced nanocomposites taking into account tunnelling effect”, J. Comput. Phys., 337, 116-131 (2017).

[3] Lu, X., Yvonnet, J., Detrez, F., Bai, J., “Low electrical percolation thresholds and nonlinear effects in graphene-reinforced nanocomposites: a numerical analysis”, J. Compos. Mater., 52, 2767-2775 (2018).

 

 [4] Lu, X., Giovanis, D. G., Yvonnet, J., Papadopoulos, V., Detrez, F., Bai, J., “A data-driven compu-tational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites”, Comp. Mech., 52, 1-15 (2018).

 

 








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