Mechanical properties of graphene nanoplatelets reinforced epikote 828 under dynamic compression

Autor: Yumna Qureshi, Mostapha Tarfaoui, H. Benyahia, S. Khammassi
Přispěvatelé: Institut de Recherche Dupuy de Lôme (IRDL), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Centre National de la Recherche Scientifique (CNRS), Conseil Régional de Bretagne
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Mechanics of Materials
Mechanics of Materials, Elsevier, 2021, 158, pp.103873. ⟨10.1016/j.mechmat.2021.103873⟩
ISSN: 0167-6636
DOI: 10.1016/j.mechmat.2021.103873⟩
Popis: International audience; In this experimental investigation, the influence of graphene nanoplatelets (GNPs) on the dynamic behavior of polymeric material such as diglycidyl ether of bisphenol A (DGEBA) epoxy is investigated using the Split Hopkinson Pressure Bar (SHPB). Nanocomposite samples with a different weight percentage of GNPs i.e. 0, 1, 2, 5 wt% were fabricated and tested under dynamic compression to understand the influence of nanofillers on the mechanical performance of the epoxy. The results established that changing the mass fraction of GNPs greatly influences the mechanical behavior of the epoxy and confirmed that the optimal mass fraction of GNPs was 1 wt% because of the good dispersion and viscosity. While, a further increase in the percentage of GNPs resulted in degradation of the mechanical strength of the material because of the agglomeration of graphene sheets, porosity, and their poor interfacial bonding. Moreover, each mass fraction of nanocomposites was tested at three different impact pressures i.e. 1.5, 2, and 4 bar. The main objective is to quantify the effect of the strain rate on the mechanical behavior and on the resulting damage modes. This study further confirmed that the high percentage of GNPs increases the viscosity of the epoxy resulting in porosity and void in the structure which generates high-localised stresses into the matrix causing premature failure under dynamic loading.
Databáze: OpenAIRE