Author
Batyrov, Merdan, Dericiler, K., Palabıyık, Büşra Akkoca, Okan, B. S., Öztürk, Hande, Fındıkçı, İlknur Eruçar
Publication Date
2023-06
Publication Place
-
Elsevier
Subject
6, Elastic modulus, Graphene, MD simulation, Polyamide-6, Polymer nanocomposite
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
2352-4928
Record ID
2c33f74a-6a4c-4f47-bf2a-2c8a85c24660
Library Location
Natural and Mathematical Sciences
Date
2023-06
Notes
High-Performance Computing Laboratory of Ozyegin University ; TÜBİTAK
Sample Text
In this work, we combined tensile test results with atomistic simulations to investigate the effect of filler parameters including distribution, stacking, loading and lateral graphene size on elastic moduli of graphene/PA-6,6 nanocomposites. Stacked and randomly distributed atomistic models were adapted in Molecular Dynamics (MD) simulations to establish the limits of stiffness enhancement in graphene reinforced PA-6,6 nanocomposites with loading ratios changing from 0 to 1 wt%. Experimental results showed that incorporating of 0.3–0.4 wt% graphene loading improved the elastic modulus of the neat polymer by 41.7%−43.5%. While the test sample behaved close to the computational results of the stacked atomistic model at low graphene loadings up to 0.4 wt%, it overshot the predictions of the randomly distributed model at all considered loadings up to 1 wt%. Elastic moduli of graphene-based PA-6,6 nanocomposites increased linearly with graphene loading in the stacked model, however, no such relation was detected in the randomly distributed model. The lower stiffness enhancement provided by the randomly distributed model compared to the stacked model was revealed as the small lateral size of graphene plates in PA-6,6 matrix. As the graphene size increased, the elastic modulus of the graphene dramatically increased, directly improving the elastic modulus of the nanocomposite. The developed computational approach is highly useful to estimate the boundaries of stiffness enhancement provided by graphene dispersions in macroscale nanocomposite samples.
DOI
10.1016/j.mtcomm.2023.105636
Cilt
35
