Physical Origin of Distinct Mechanical Properties of Polymer Tethered Graphene Nanosheets Reinforced Polymer Nanocomposites Revealed by Nonequilibrium Molecular Dynamics Simulations

Abstract

A non-equilibrium deformation simulation based on standard molecular dynamics is employed to reveal the physical origin of distinct mechanical properties of polymer nanocomposites (PNCs) reinforced by polymer tethered graphene nanosheets (P/G-T). The effect of tethered polymer length (L) and interaction strength on the mechanical properties, including tensile stress, modulus, and yield strength, are examined. The simulation results show that the P/G-T systems exhibit improved mechanical properties as L and interaction strength increases. The strengthening in attractive interaction between matrix polymer and tethered polymer has a better effect on mechanical properties than that between P and graphene nanosheets. It is found that the bond orientation and nonbonding potential is of crucial importance in determining the mechanical properties of the P/G-T nanocomposite systems. The calculations of radial distribution functions and mean-squared displacement are further performed to reveal the physical origin of enhanced mechanical properties, suggesting that the stronger interfacial interactions will induce the closer packing distance with smaller free volume, higher polymer chain entanglement, and higher restriction of polymer chain movement, which synergistically contribute to the improvement in the mechanical properties. The results may provide useful guidance for promoting the development and practical application of the advanced PNCs with excellent performance.

Structure and properties of polymer/two-dimensional nanomaterials studied via molecular dynamics simulation: a review

“…Graphene has received preferred attention as reinforcement in polymer composites based on MD simulation. 42–44 Lin et al constructed 45 graphene stacked models with large size and planar orientation which are fully exfoliated in the poly (methyl methacrylimide) (PMMA) matrix (Fig. 3(a)), and revealed that Young's modulus and shear modulus increase monotonically, while the enhancement efficiency gradually decreases with the filling loading of graphene, and simultaneously mechanical properties decrease with an increase in temperature from 300 to 500 K. Zhang et al 46 adopted an optimized Tersoff potential and constructed a graphene/poly (3-hexylthiophene) (P3HT) concentration model; they found that the elastic modulus and strength of the 5% graphene/95% P3HT composite can reach 1.5 GPa and 90 MPa, which is around 1.5 times compared to the pure matrix.…”

Synthesis of Nickel Spinel Ferrites Nanoparticles Coated with Thermally Reduced Graphene Oxide for EMI Shielding in the Microwave, UV, and NIR Regions

“…EMI shielding of NiFe and TRGO was also tested separately in previous work. NiFe has poor dispersibility in a polymer matrix and gave almost 30 dB shielding effectiveness at 20 wt.% loading, while TRGO has good dispersibility and gave almost 35 dB shielding effectiveness with 5 wt.% loading [30][31][32]. The scattering parameter represents S11 as the coefficient of forwarding reflection, S12 as the coefficient of reverse transmittance, and S21 represents the coefficient of forwarding transmission.…”

“…% loading, while TRGO has good dispersibility and gave almost 35 dB shielding effectiveness with 5 wt. % loading [30][31][32].…”

“…Zubair et al synthesized thermally reduced graphene oxide (TRGO) and barium ferrites (BaFe) nanocomposites to improve the shielding efficiency solution casting method. A shielding efficiency of 62 dB was obtained at 12.5 GHz with improved conductivity values of 4.8 × 10 −5 [31]. In another work, Shakir et al, synthesized NiFe to evaluate the effect on EMI shielding.…”

Radial point interpolation‐Chebychev method with asymptotic numerical method for nonlinear buckling analysis of graphene oxide powder‐reinforced composite beams

“…There have been several works that have focused on simulating the properties and behavior of graphene oxide powder (GOP) composite structures. These simulations are often performed using computational methods such as molecular dynamics (MD), 9,10 finite element analysis (FEA), 11,12 meshless methods [13][14][15][16][17] and analytical solution. 18,19 One area of focus in these simulations is on understanding the behavior of the graphene oxide powder within the composite material.…”