Characterisation of melt processed nanocomposites of Polyamide 6 subjected to uniaxial-drawing

In this paper, the processing and characterization of Polyamide 6 (PA6) nanocomposites containing graphite nanoplatelets (GNPs) is reported. PA6 nanocomposites were prepared by melt-mixing using an industrial, co-rotating, intermeshing, twin-screw extruder. A bespoke screw configuration was used that was designed in-house to enhance nanoparticle dispersion into a polymer matrix. The effects of nano-filler type (xGnPTM M-5 and xGnPTM C-500), nano-filler content, and extruder screw speed on the bulk properties of the PA6 nanocomposites were investigated. The crystalline structures of PA6 nanocomposites are related to thermal treatment, stress history and the presence of moisture and nanofillers. DSC, Raman and XRD studies show an increase in crystallinity with increasing GNP content and a phase transformation between α-form to γ-form crystals as a result of the heterophase nucleation effect. The effect of uniaxial stretching on PA6 nanocomposites was investigated by drawing specimens heated at temperatures below the melting temperature. DSC and Raman studies on the drawn samples show an increase in yield stress as the GNP content increases due to the strain induced crystallization and γ—β transition during stretching. The rheological response of the nanocomposites resemble that of a ‘pseudo-solid’, rather than a molten liquid, and analysis of the rheological data indicates that a percolation threshold was reached at GNP contents of between 10–15wt%. An increase in tensile modulus of as much as 412% was observed for PA6/C-500 xGnPTM composites, at a filler content of 20wt%. The enhancement of Young’s modulus and yield stress can be attributed to the reinforcing effect of GNPs and their uniform dispersion in the PA6 matrix. The electrical conductivity of the composite also increased with increasing GNP content, with an addition of 15wt% GNP resulting in a 6 order-of-magnitude increase in conductivity. The effects of uniaxial-drawing and the inclusion of multiple nano-filler varieties on the electrical and mechanical properties are currently under investigation.

Melt processing and properties of linear low density polyethylene-graphene nanoplatelet composites

Composites of Linear Low Density Polyethylene (LLDPE) and Graphene Nanoplatelets (GNPs) were processed using a twin screw extruder under different extrusion conditions. The effects of screw speed, feeder speed and GNP content on the electrical, thermal and mechanical properties of composites were investigated. The inclusion of GNPs in the matrix improved the thermal stability and conductivity by 2.7% and 43%, respectively. The electrical conductivity improved from 10−11 to 10−5 S/m at 150 rpm due to the high thermal stability of the GNPs and the formation of phonon and charge carrier networks in the polymer matrix. Higher extruder speeds result in a better distribution of the GNPs in the matrix and a significant increase in thermal stability and thermal conductivity. However, this effect is not significant for the electrical conductivity and tensile strength. The addition of GNPs increased the viscosity of the polymer, which will lead to higher processing power requirements. Increasing the extruder speed led to a reduction in viscosity, which is due to thermal degradation and/or chain scission. Thus, while high speeds result in better dispersions, the speed needs to be optimized to prevent detrimental impacts on the properties.

Partial exfoliation of layered double hydroxides in DMSO : a route to transparent polymer nanocomposites

Layered double hydroxides (LDHs), either having nitrate counter anions or intercalated with organic molecules, have been for the first time partially exfoliated in dimethyl sulfoxide (DMSO) to form a transparent suspension. Atomic force microscopy (AFM) images showed that both the lateral size and the thickness of the LDH nanoplatelets were decreased after the exfoliation. The organic-LDHs maintained their intercalation characteristics, i.e. the thermal stability improvement of the incorporated organic anions, after the exfoliation in DMSO. Transparent ethylene-vinyl alcohol copolymer (EVOH) nanocomposite films containing partially exfoliated LDHs intercalated with UV absorbers were prepared using DMSO as the processing solvent. As the first reported example of a highly transparent LDH/polymer composite, the obtained composite film had a visible light transmittance of 90% (comparable to that of the pure matrix), was flexible and exhibited an excellent UV-shielding capability and thermal stability.

High N-content holey few-layered graphene electrocatalysts: Scalable solvent-less production

Few layered nitrogen doped graphene (NG) attracts great interest in energy storage and conversion applications due to its electronic and catalytic properties. However, its bulk production cannot be envisioned by the current synthetic methods. Here we report a facile, solvent-less, low cost and high yield process for the synthesis of NG. Mechanochemical solid-state exfoliation allows scalable synthesis of holey and crumple nitrogen-doped few-layered graphene from graphite with controlled high concentration N doping and a high surface area through ball-milling. By adjusting the ratio of starting materials, the nitrogen content can be modulated from 4.87 to 17.83 at.%. Furthermore, the types of nitrogen-containing species in few-layered graphene can also be controlled. The resultant NG exhibits superior oxygen reduction reaction performance and more reliable stability than commercial Pt/C catalysts. This journal is

Graphene networks and their influence on free-volume properties of graphene-epoxidized natural rubber composites with a segregated structure: rheological and positron annihilation studies

Epoxidized natural rubber-graphene (ENR-GE) composites with segregated GE networks were successfully fabricated using the latex mixing combined in situ reduced technology. The rheological behavior and electrical conductivity of ENR-GE composites were investigated. At low frequencies, the storage modulus (G′) became frequency-independent suggesting a solid-like rheological behavior and the formation of GE networks. According to the percolation theory, the rheological threshold of ENR-GE composites was calculated to be 0.17 vol%, which was lower than the electrical threshold of 0.23 vol%. Both percolation thresholds depended on the evolution of the GE networks in the composites. At low GE concentrations (<0.17 vol%), GE existed as individual units, while a "polymer-bridged GE network" was constructed in the composites when GE concentrations exceeded 0.17 vol%. Finally, a "three-dimensional GE network" with percolation conductive paths was formed with a GE concentration of 0.23 vol%, where a remarkable increase in the conductivity of ENR-GE composites was observed. The effect of GE on the atom scale free-volume properties of composites was further studied by positron annihilation lifetime spectroscopy and positron age momentum correlation measurements. The motion of ENR chains was retarded by the geometric confinement of "GE networks", producing a high-density interfacial region in the vicinity of GE nanoplatelets, which led to a lower ortho-positronium lifetime intensity and smaller free-volume hole size.

Multifunctional properties of epoxy nanocomposites reinforced by aligned nanoscale carbon

The present paper compares improvements to the fracture energy and electrical conductivity of epoxy nanocomposites reinforced by one-dimensional carbon nanofibres (CNFs) or two-dimensional graphene nanoplatelets (GNPs). The focus of this investigation is on the effects of the shape, orientation and concentration (i.e. 0.5, 1.0, 1.5 and 2.0 wt%) of nanoscale carbon reinforcements on the property improvements. Alignment of the nano-reinforcements in the epoxy nanocomposites was achieved through the application of an alternating current (AC) electric-field before gelation and curing of the epoxy resin. Alignment of the nano-reinforcements increased the electrical conductivity and simultaneously lowered the percolation threshold necessary to form a conductive network in the nanocomposites. Nano-reinforcement alignment also increased greatly the fracture energy of the epoxy due to a higher fraction of the nano-reinforcement participating in multiple intrinsic (e.g. interfacial debonding and void growth) and extrinsic (e.g. pull-out and bridging) toughening mechanisms. A mechanistic model is presented to quantify the contributions from the different toughening mechanisms induced by CNFs and GNPs to the large improvements in fracture toughness. The model results show that one-dimensional CNFs are more effective than GNPs at increasing the intrinsic toughness of epoxy via void growth, whereas two-dimensional GNPs are more effective than CNFs at improving the extrinsic toughness via crack bridging and pull-out.

Epoxy nanocomposites with aligned carbon nanofillers by external electric fields

This paper presents systematic studies on aligning carbon nanofillers in epoxy by external fields, either electric fields or magnetic fields, to create nanocomposites with greatly improved mechanical and electrical properties. Carbon nanofibers (CNFs) and graphene nanoplatelets (GnPs) were observed to align along the field direction in the epoxy resin. Compared to the unmodifed epoxy and those with randomly-oriented carbon nanofillers, the nanocomposites with aligned carbon nanofillers showed significantly higher fracture toughness and electrical conductivity along the direction of the external field. Compared with randomly-oriented nanofillers, aligned GnPs and CNFs produced 40% and 27% improvement in fracture energy at 1.0 wt%, bringing the total increase in fracture energy over the neat polymer to more than 10 times. Several key toughening mechanisms were identified through fractographic analysis, which was used to develop predictive models to quantify the increases in the value of GIc as a result of 1-D and 2D carbon nanofillers. The present findings suggest that aligning carbon nanofillers presents a very promising technique to create multi-scale reinforcement with greatly increased electric conductivity and fracture toughness.

A novel route for tethering graphene with iron oxide and its magnetic field alignment in polymer nanocomposites

We present a new route of tethering graphene nanoplatelets (GNPs) with Fe3O4 nanoparticles to enable their alignment in an epoxy using a weak magnetic field. The GNPs are first stabilised in water using polyvinylpyrrolidone (PVP) and Fe3O4 nanoparticles are then attached via co-precipitation. The resultant Fe3O4/PVP-GNPs nanohybrids are superparamagnetic and can be aligned in an epoxy resin, before gelation, by applying a weak magnetic field as low as 0.009 T. A theoretical model describing the alignment process is presented and used to quantify the effects of key parameters on the time needed for the alignment process. Compared to the unmodified epoxy, the resulting epoxy polymer nanocomposites containing randomly-oriented Fe3O4/PVP-GNPs nanohybrids exhibit significantly improved electrical conductivities by up to three orders of magnitude and fracture energies by up to 300%. The alignment of the Fe3O4/PVP-GNPs nanohybrids in the epoxy polymer nanocomposites transverse to the direction of crack propagation further increased the fracture energy by 50%, and the electrical conductivity by seven fold in the alignment direction, compared to the nanocomposites containing randomly-oriented nanohybrids.

Simulação da nanoestruturação de nanofolhas de óxido de grafeno reduzido através de dinâmica molecular

Pós-graduação em Ciência e Tecnologia de Materiais - FC

Formation of an extended CoSi2 thin nanohexagons array coherently buried in silicon single crystal

A Co-doped silica film was deposited on the surface of a Si(100) wafer and isothermally annealed at 750 degrees C to form spherical Co nanoparticles embedded in the silica film and a few atomic layer thick CoSi2 nanoplatelets within the wafer. The structure, morphology, and spatial orientation of the nanoplatelets were characterized. The experimental results indicate that the nanoplatelets exhibit hexagonal shape and a uniform thickness. The CoSi2 nanostructures lattice is coherent with the Si lattice, and each of them is parallel to one of the four planes belonging to the {111} crystallographic form of the host lattice. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683493]

Investigation into the enhancement of polycarbonate with conductive nanomaterials

Polymers are typically electrically and thermally insulating materials. The electrical and thermal conductivities of polymers can be increased by the addition conductive fillers such as carbons. Once the polymer composites have been made electrically and thermally conductive, they can be used in applications where these conductivities are desired such as electromagnetic shielding and static dissipation. In this project, three carbon nanomaterials are added to polycarbonate to enhance the electrical and thermal conductivity of the resulting composite. Hyperion Catalysis FIBRILs carbon nanotubes were added to a maximum loading of 8 wt%. Ketjenblack EC-600 JD carbon black was added to a maximum loading of 10 wt%. XG Sciences xGnP™ graphene nanoplatelets were added to a maximum loading of 15 wt%. These three materials have drastically different morphologies and will have varying effects on the various properties of polycarbonate composites. It was determined that carbon nanotubes have the largest effect on electrical conductivity with an 8 wt% carbon nanotube in polycarbonate composite having an electrical conductivity of 0.128 S/cm (from a pure polycarbonate value of 10-17 S/cm). Carbon black has the next largest effect with an 8 wt% carbon black in polycarbonate composite having an electrical conductivity of 0.008 S/cm. Graphene nanoplatelets have the least effect with an 8 wt% graphene nanoplatelet in polycarbonate having an electrical conductivity of 2.53 x 10-8 S/cm. Graphene nanoplatelets show a significantly higher effect on increasing thermal conductivity than either carbon nanotubes or carbon black. Mechanically, all three materials have similar effects with graphene nanoplatelets being somewhat more effective at increasing the tensile modulus of the composite than the other fillers. Carbon black and graphene nanoplatelets show standard carbon-filler rheology where the addition of filler increases the viscosity of the resulting composite. Carbon nanotubes, on the other hand, show an unexpected rheology. As carbon nanotubes are added to polycarbonate the viscosity of the composite is reduced below that of the original polycarbonate. It was seen that the addition of carbon nanotubes offsets the increased viscosity from a second filler, such as carbon black or graphene nanoplatelets.

Oxygen evolution at ultrathin nanostructured Ni(OH)2 layers deposited on conducting glass

Ultrathin and transparent nanostructured Ni(OH)2 films were deposited on conducting glass (F:SnO2) by a urea-based chemical bath deposition method. By controlling the deposition time, the amount of deposited Ni(OH)2 was varied over 7 orders of magnitude. The turnover number for O2 generation, defined as the number of O2 molecules generated per catalytic site (Ni atom) and per second, increases drastically as the electrocatalyst amount decreases. The electrocatalytic activity of the studied samples (measured as the current density at a certain potential) increases with the amount of deposited Ni(OH)2 until a saturation value is already obtained for a thin film of around 1 nm in thickness, composed of Ni(OH)2 nanoplatelets lying flat on the conductive support. The deposition of additional amounts of catalyst generates a porous honeycomb structure that does not improve (only maintains) the electrocatalytic activity. The optimized ultrathin electrodes show a remarkable stability, which indicates that the preparation of highly transparent electrodes, efficient for oxygen evolution, with a minimum amount of nickel is possible.

A Comparison Between Graphene and WS2 as Solid Lubricant Additives to Aluminum for Automobile Applications

The purpose of this thesis was to compare graphene nanoplatelets (GNP) and WS2 as solid lubricant additives to aluminum in order to reduce friction and wear. The central hypothesis of this work relied on lubricating properties of 2D materials, which consist layers that slip under a shear force. Two aluminum composites were made (Al-2 vol.% GNP and Al-2 vol.% WS2) by spark plasma sintering. Tribological properties were evaluated by ball-on-disk wear tests at room temperature (RT) and 200°C. WS2 not only presented the lowest COF (0.66) but also improved the wear resistance of aluminum by 54% at RT. Al-2 vol.% GNP composite displayed poor densification (91%) and low hardness resulting in poor wear resistance. The wear rate of Al-2 vol.% GNP composite increased by 233% at RT and 48% at 200°C as compared to pure aluminum. GNP addition also resulted in lower COF (0.79) as compared to pure aluminum (0.87).

Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks

The focus of this work is to develop the knowledge of prediction of the physical and chemical properties of processed linear low density polyethylene (LLDPE)/graphene nanoplatelets composites. Composites made from LLDPE reinforced with 1, 2, 4, 6, 8, and 10 wt% grade C graphene nanoplatelets (C-GNP) were processed in a twin screw extruder with three different screw speeds and feeder speeds (50, 100, and 150 rpm). These applied conditions are used to optimize the following properties: thermal conductivity, crystallization temperature, degradation temperature, and tensile strength while prediction of these properties was done through artificial neural network (ANN). The three first properties increased with increase in both screw speed and C-GNP content. The tensile strength reached a maximum value at 4 wt% C-GNP and a speed of 150 rpm as this represented the optimum condition for the stress transfer through the amorphous chains of the matrix to the C-GNP. ANN can be confidently used as a tool to predict the above material properties before investing in development programs and actual manufacturing, thus significantly saving money, time, and effort.