3D RVE Models Able to Capture and Quantify the Dispersion, Agglomeration, and Orientation State of CNT in CNT/PP Nanocomposites

Abstract

The focus of this study is to investigate the capabilities of three dimensional (3D) RVE models in predicting the tensile modulus of carbon nanotube/polypropylene (CNT/PP) composites, which differ slightly in the dispersion, agglomeration, and orientation states of CNT within the PP matrix. The composites are made using melt mixing followed by either injection molding or melt spinning of fibers. The dispersion, agglomeration, and orientation of CNT within the PP are experimentally altered by using a surfactant and by forcing the molten material to flow through a narrow orifice (melt spinning) that promotes alignment of CNT along the flow/drawing direction. An elaborate image analysis technique is used to quantify the CNT characteristics in terms of probability distribution functions (PDF). The PDF are then introduced to the 3D RVE models that also account for the CNT-PP interfacial interactions. It is concluded that the 3D RVE models can accurately distinguish among the different cases (dispersion, distribution, geometry, and alignment of CNT) as the predicted tensile modulus is in good agreement with the experimentally determined one.

Three-Dimensional Stochastic Modelling of Wavy Carbon Nanotube Reinforced Epoxy Nanocomposites

“…Considering several cases by varying the parameters, they concluded the CNT alignment to be a more influencing parameter than the CNT waviness while predicting elastic properties of random CNT composites. It is further supported by results obtained by Bhuyian et al [14,27] who also incorporated less-studied parameters such as a soft CNT/polymer interphase and CNT agglomeration. Fiber/matrix interface has been discussed to be of importance by Reifsnider et al [1].…”

“…The theoretical, experimental and multiscale modelling aspects of CNT based polymer composites are reviewed extensively by [6][7][8][9][10][11]. Depending upon the CNT orientation, there can be random [12][13][14][15][16] as well as aligned [17][18][19][20] CNT composites. Previous studies found that the properties of these composites are greatly influenced by the morphological parameters such as CNT orientation, dispersion, waviness, diameter, inter-CNT spacing, etc.…”

“…Several researchers confirmed that the increase in the density of the polymer matrix in the vicinity of the fiber reinforcement [41][42][43][44] as well as the increased covalent bonding at the interface due to the surface functionalization of the fibers [42,44] can lead to the formation of a 'hard' interphase. Later in their studies, Bhuyian et al [14,27,45,46] used AFM and SEM to confirm the presence of voids, and hence represented CNT/matrix interphase as a 'soft' interphase.…”

Improved hemostatic effects by Fe3+ modified biomimetic PLLA cotton-like mat via sodium alginate grafted with dopamine

“…Therefore, the polymer of PLLA was melted uniformly and the melt flow rate of PLLA achieves stability [ 46 , 47 ]. However, the melt of PLLA polymer would be cooled agglomeration as it flow to the end of the 840 μm spinneret due to its temperature of the 840 μm spinneret lower glass conversion temperature of PLLA polymer [ 48 ]. We can observe that the diameter of fibre became tiny with receiving distance increased when 840 μm spinneret was used.…”

Calculating the effective thermal conductivity of gray cast iron by using an interconnected graphite model

“…Unit cell model applies a representative volume element (RVE) composed of phases with different thermal conductivities, and the thermal conductivity of RVE is calculated according to the thermal resistance network method [17] . This model is also widely used in numerical simulation [18,19] . Zehner et al [20] calculated the thermal conductivity of the point-contacted spherical particle reinforced composites by constructing a cylindrical unit cell.…”