Nonlinear “oddities” at the percolation of 3D hierarchical graphene polymer nanocomposites

Kádár, Roland; Gąska, Karolina; Gkourmpis, Thomas

doi:10.1007/s00397-020-01204-w

Cited by 13 publications

(27 citation statements)

References 48 publications

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“…Here we must note that our experimental data exhibits with a steep increase up to the percolation threshold~1 wt.% [27,77]. Beyond that point the increase of the modulus is fairly restricted, something that can possibly be associated with the increased number of agglomerates as the filler content increases [17].…”

Section: Micromechanical Modellingmentioning

confidence: 66%

“…

where W is the average width of the filler (taken ~2–3 μm in our case), L the average length (4–10 μm), and t the average thickness (0.34–0.71 nm). The parameters used in this work are based on the characterization of the filler [ 27 , 77 ]. The filler volumes fraction can be determined from using the matrix ( ρ M ) and filler densities ( ρ F ) and the filler weight fraction (

) as:

where V F = 1 − V M , V M being the matrix volume fraction.…”

Section: Resultsmentioning

confidence: 99%

“…Beyond that point the increase of the modulus is fairly restricted, something that can possibly be associated with the increased number of agglomerates as the filler content increases [17]. This is expected to have a detrimental effect on the load transfer between the filler and the matrix as the system is having reduced opportunities to get access to the primary particles, something that can be associated both with the electrical conductivity that reaches an almost saturation level [27] and the flow behavior of the material [77].…”

Section: Micromechanical Modellingmentioning

confidence: 99%

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Mechanical Behavior of Melt-Mixed 3D Hierarchical Graphene/Polypropylene Nanocomposites

et al. 2020

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The mechanical properties of novel low percolation melt-mixed 3D hierarchical graphene/polypropylene nanocomposites are analyzed in this study. The analysis spans a broad range of techniques and time scales, from impact to tensile, dynamic mechanical behavior, and creep. The applicability of the time–temperature superposition principle and its limitations in the construction of the master curve for the isotactic polypropylene (iPP)-based graphene nanocomposites has been verified and presented. The Williams–Landel–Ferry method has been used to evaluate the dynamics and also Cole–Cole curves were presented to verify the thermorheological character of the nanocomposites. Short term (quasi-static) tensile tests, creep, and impact strength measurements were used to evaluate the load transfer efficiency. A significant increase of Young’s modulus with increasing filler content indicates reasonably good dispersion and adhesion between the iPP and the filler. The Young’s modulus results were compared with predicted modulus values using Halpin–Tsai model. An increase in brittleness resulting in lower impact strength values has also been recorded.

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Section: Micromechanical Modellingmentioning

confidence: 66%

“…

) as:

where V F = 1 − V M , V M being the matrix volume fraction.…”

Section: Resultsmentioning

confidence: 99%

Section: Micromechanical Modellingmentioning

confidence: 99%

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Mechanical Behavior of Melt-Mixed 3D Hierarchical Graphene/Polypropylene Nanocomposites

et al. 2020

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“…This potentially corresponds to the existence of a weakly formed filler network that is disrupted by the shear flow. A more thorough analysis and further discussion on the interpretation of the nonlinear data in terms of rheological and electrical percolation thresholds, as well as potential nanocomposite morphological fingerprinting is discussed elsewhere [73]. The instrument noise at low strain amplitudes has been excluded from the graphs, see Figure 2.…”

Section: Melt Rheologymentioning

confidence: 99%

Melt-Mixed 3D Hierarchical Graphene/Polypropylene Nanocomposites with Low Electrical Percolation Threshold

et al. 2019

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Graphene-based materials are a family of carbonaceous structures that can be produced using a variety of processes either from graphite or other precursors. These materials are typically a few layered sheets of graphene in the form of platelets and maintain some of the properties of pristine graphene (such as two-dimensional platelet shape, aspect ratio, and graphitic bonding). In this work we present melt mixed graphene-based polypropylene systems with significantly reduced percolation threshold. Traditionally melt-mixed systems suffer from poor dispersion that leads to high electrical percolation values. In contrast in our work, graphene was added into an isotactic polypropylene matrix, achieving an electrical percolation threshold of~1 wt.%. This indicates that the filler dispersion process has been highly efficient, something that leads to the suppression of the β phase that have a strong influence on the crystallization behavior and subsequent thermal and mechanical performance. The electrical percolation values obtained are comparable with reported solution mixed systems, despite the use of simple melt mixing protocols and the lack of any pre or post-treatment of the final compositions. The latter is of particular importance as the preparation method used in this work is industrially relevant and is readily scalable.

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“…This observation suggests that GN/PCL composites experience a more substantial shear‐thinning effect than that of the pure PCL, which is consistent with the experimental results. [ 31 ] From the microstructure perspective, the alignment and stacking of GNs can lower the viscosity and introduce a more significant shear‐thinning effect than that of pure PCL. Although the difference is not significant, the effects of GN size and layer number are quite consistent with the equilibrium simulation results but on a smaller scale.…”

Section: Resultsmentioning

confidence: 99%

Atomistic Insights on the Rheological Property of Polycaprolactone Composites with the Addition of Graphene

Nie

Zhan

Kou

et al. 2021

Adv Materials Technologies

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Although polymer composites reinforced by graphene have been researched for almost two decades, the processing challenges caused by viscosity remains, especially for 3D printing. [3] Many experimental works have been conducted to assess the rheological properties of graphene reinforced composites, covering various factors such as weight/volume fraction, dispersion, surface modification, and shear rate. [4] However, the influence of the graphene size has not been systematically studied experimentally due to the intrinsic complexities and challenges for sample preparation with controlled micro/nanoscale features. In particular, the influence of 2D nanoscale fillers on the rheological properties of polymer composites remains unclear. With such experimental difficulties, numerical modeling or simulation becomes a powerful tool to probe the rheological properties of polymer composites at the micro and nano scales. Different modeling approaches have been developed for such purposes, such as the multiscale method, coarse grain (CG) method, and molecular dynamic (MD) simulation. For instance, the multiscale method has been well-developed to predict the mechanical performance of carbon-reinforced composites. [5] Compared with the multiscale and CG methods, MD simulation can exploit the influences from nanoscale reinforcements on the rheological properties of polymer composites at an atomistic level. Many works have investigated the effect of the size of nanoparticle reinforcements on the composite's viscosity based on MD simulations. Grant et al. [6] identified that viscosity could be influenced by the nanoparticle volume fraction, interface area, and the interaction between particle and polymer. Francis et al. [7] found that the composite viscosity would decrease when small particles aggregate into a large cluster. More recent work found that the composite viscosity depends on the relation between particle size and polymer entanglement length. Jagannathan et al. [8] discovered that if the particle size is smaller than the polymer entanglement length, the composite viscosity will reduce and vice versa. Ting et al. [9] chose a group of particles smaller than the polymer entanglement length and found that the viscosity increases with increasing particle size while the interaction between the polymer and particle changes from slippery to sticky. Overall, when the particle size is around the polymer entanglement length, the viscosity increases with To facilitate the biomedical applications of biocomposites, researchers have used different types of fillers to enhance their mechanical properties. However, the addition of fillers not only changes the mechanical performance of the biocomposites, but also affects their printability, that is, their rheological properties. With the aid of atomistic simulations, this work investigates the influence of graphene size and aggregation on the rheological properties of polycaprolactone (PCL) composites. For the same weight ratio, increasing the graphene size causes the viscosity of the ...

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Nonlinear “oddities” at the percolation of 3D hierarchical graphene polymer nanocomposites

Cited by 13 publications

References 48 publications

Mechanical Behavior of Melt-Mixed 3D Hierarchical Graphene/Polypropylene Nanocomposites

Mechanical Behavior of Melt-Mixed 3D Hierarchical Graphene/Polypropylene Nanocomposites

Melt-Mixed 3D Hierarchical Graphene/Polypropylene Nanocomposites with Low Electrical Percolation Threshold

Atomistic Insights on the Rheological Property of Polycaprolactone Composites with the Addition of Graphene

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