Composites of LDPE filled with different amounts of graphene nanoplatelets (GnP) were prepared in form of films by means of precoating technique and single screw melt-extrusion using two types of ...screws, compression and mixing. This manufacturing process imposes strong anisotropy on the sample's morphology, in which the nanoplatelets become oriented along the extrusion direction. Such orientation of GnP in LDPE matrix is confirmed by scanning electron microscopy observations and it yields unique electrical properties. As compared to pure LDPE, significant reductions of the through-plane conductivity are found for the composites at relatively low electric fields (<20 kV/mm) at low filler concentrations. Above the field level of 20 kV/mm, a crossover effect is observed that results in a strong field dependency of the conductivity where the non-linear behavior starts to dominate. Moreover, differential scanning calorimetry (DSC) results indicate a decrease in polymer crystallinity of the composite matrix with increasing filler content, whereas thermogravimetric (TG) analysis shows a slight increase in the material's thermal stability. Application of GnP also leads to improvement of mechanical properties, manifested by the increase of Young's modulus and tensile strength in both types of samples.
The nonlinear rheology of a novel 3D hierarchical graphene polymer nanocomposites was investigated in this study. Based on an isotactic polypropylene, the nanocomposites were prepared using simple ...melt mixing, which is an industrially relevant and scalable technique. The novel nanocomposites stand out as having an electrical percolation threshold (≈0.94 wt%) comparable to solution mixing graphene-based polymer nanocomposites. Their nonlinear flow behavior was investigated in oscillatory shear via Fourier-transform (FT) rheology and Chebyshev polynomial decomposition. It was shown that in addition to an increase in the magnitude of nonlinearities with filler concentration, the electrical percolation threshold corresponds to a unique nonlinear rheological signature. Thus, in dynamic strain sweep tests, the nonlinearities are dependent on the applied angular frequency, potentially detecting the emergence of a weakly connected network that is being disrupted by the flow. This is valid for both the third relative higher harmonic from Fourier-transform rheology,
I
3/1
, as well as the third relative viscous,
v
3/1
, Chebyshev coefficient. The angular frequency dependency comprised non-quadratic scaling in
I
3/1
with the applied strain amplitude and a sign change in
v
3/1
. The development of the nonlinear signatures was monitored up to concentrations in the conductor region to reveal the influence of a more robust percolated network.
Bacteria are known to form biofilms on various surfaces. Biofilms are multicellular aggregates, held together by an extracellular matrix, which is composed of biological polymers. Three principal ...components of the biofilm matrix are exopolysaccharides (EPS), proteins, and nucleic acids. The biofilm matrix is essential for biofilms to remain organized under mechanical stress. Thanks to their polymeric nature, biofilms exhibit both elastic and viscous mechanical characteristics; therefore, an accurate mechanical description needs to take into account their viscoelastic nature. Their viscoelastic properties, including during their growth dynamics, are crucial for biofilm survival in many environments, particularly during infection processes. How changes in the composition of the biofilm matrix affect viscoelasticity has not been thoroughly investigated. In this study, we used interfacial rheology to study the contribution of the EPS component of the matrix to viscoelasticity of
biofilms. Two strategies were used to specifically deplete the EPS component of the biofilm matrix, namely (i) treatment with sub-lethal doses of vitamin C and (ii) seamless inactivation of the
operon responsible for biosynthesis of the EPS. In both cases, the obtained results suggest that the EPS component of the matrix is essential for maintaining the viscoelastic properties of bacterial biofilms during their growth. If the EPS component of the matrix is depleted, the mechanical stability of biofilms is compromised and the biofilms become more susceptible to eradication by mechanical stress.
An effective model to calculate thermal conductivity of polymer composites using core-shell fillers is presented, wherein a core material of filler grains is covered by a layer of a ...high-thermal-conductivity (HTC) material. Such fillers can provide a significant increase of the composite thermal conductivity by an addition of a small amount of the HTC material. The model employs the Lewis-Nielsen formula describing filled systems. The effective thermal conductivity of the core-shell filler grains is calculated using the Russel model for porous materials. Modelling results are compared with recent measurements made on composites filled with cellulose microbeads coated with hexagonal boron nitride (h-BN) platelets and good agreement is demonstrated. Comparison with measurements made on epoxy composites, using silver-coated glass spheres as a filler, is also provided. It is demonstrated how the modelling procedure can improve understanding of properties of materials and structures used and mechanisms of thermal conduction within the composite.
This contribution reports on properties of low-density polyethylene-based composites filled with different amounts of graphene nanoplatelets. The studied samples were prepared in the form of films by ...means of the precoating technique and single screw melt-extrusion, which yields a highly ordered arrangement of graphene flakes and results in a strong anisotropy of composites morphology. The performed tests of gas permeability reveal a drastic decrease of this property with increasing filler content. A clear correlation is found between permeability and free volume fraction in the material, the latter evaluated by means of positron annihilation spectroscopy. A strong anisotropy of the thermal conductivity is also achieved and the thermal conductivity along the extrusion direction for samples filled with 7.5 wt % of GnP (graphene nanoplatelets) reached 2.2 W/m·K. At the same time, when measured through a plane, a slight decrease of thermal conductivity is found. The use of GnP filler leads also to improvements of mechanical properties. The increase of Young's modulus and tensile strength are reached as the composites become more brittle.
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.
Filled epoxy composites are broadly used in electronic and power devices as an electrical insulation. It is of importance to achieve efficient heat dissipation in such devices due to fact that ...thermal properties have a strong influence on their proper operation. For this reason, the modification of standard filler materials, such as silica or alumina, can give a promising solution. In this work, a novel core–shell material has been proposed and manufactured by means of a carbothermal reduction and nitridation process. The obtained fillers are made of a standard material which is covered by the high thermally conductive shell. The synthesized fillers were characterized by means of X-ray diffraction, and scanning electron microscopy coupled with elemental analysis. The composite samples based on epoxy resin filled with the manufactured core–shell fillers have been investigated in order to determine their effective thermal conductivity. The obtained composite samples exhibited a significant improvement in the thermal conductivity, represented by a 63 % relative increase. The obtained results show the potential for the novel core–shell fillers to be applied for the electrical insulation with the enhanced thermal conductivity.
Graphene nanosheets and thicker graphite nanoplatelets are being used as reinforcement in polymeric materials to improve the material properties or induce new functional properties. By improving ...dispersion, de-agglomerating the particles, and ensuring the desired orientation of the nano-structures in the matrix, the microstructure can be tailored to obtain specific material properties. A novel surface image assisted modeling framework is proposed to understand functional properties of the graphene enhanced polymer. The effective thermal and mechanical responses are assessed based on computational homogenization. For the mechanical response, the 2-D nanoplatelets are modeled as internal interfaces that store energy for membrane actions. The effective thermal response is obtained similarly, where 2-D nanoplatelets are represented using regions of high conductivity. Using the homogenization simulation, macroscopic stiffness properties and thermal conductivity properties are modeled and then compared to the experimental data. The proposed surface image assisted modeling yields reasonable effective mechanical and thermal properties, where the Kapitza effect plays an important part in effective thermal properties.
Biomedical application of graphene derivatives have been intensively studied in last decade. With the exceptional structural, thermal, electrical, and mechanical properties, these materials have ...attracted immense attention of biomedical scientists to utilize graphene derivatives in biomedical devices to improve their performance or to achieve desired functions. Surfaces of graphene derivatives including graphite, graphene, graphene oxide and reduce graphene oxide have been demonstrated to pave an excellent platform for antimicrobial behavior, enhanced biocompatibility, tissue engineering, biosensors and drug delivery. This review focuses on the recent advancement in the research of biomedical devices with the coatings or highly structured polymer nanocomposite surfaces of graphene derivatives for antimicrobial activity and sterile surfaces comprising an entirely new class of antibacterial materials. Overall, we aim to highlight on the potential of these materials, current understanding and knowledge gap in the antimicrobial behavior and biocompatibility to be utilized of their coatings to prevent the cross infections.
Recent advances in the research of biomedical devices with coatings or highly structured polymer nanocomposites composed of graphene derivatives for self‐cleaning surfaces are reviewed. Overall, the authors aim to highlight the potential of these materials as well as the current understanding and knowledge gaps regarding their antimicrobial behavior and biocompatibility for use as biomedical coatings to prevent cross infections.
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This paper explores methods to investigate voids and dry fibre areas in pre-impregnated aligned carbon fibre reinforced epoxy lay-ups. A deep learning segmentation approach was ...compared to conventional thresholding techniques to characterise the interlaminar voids (entrapped air) and dry areas (unsaturated fibre bed) phases obtained by micro-CT scanning of samples from uncured laminates. The performance of both approaches was quantitatively assessed in three regions of interest having different levels of porosity, ranging from a low 1% to a high 25%. Deep learning consistently outperformed thresholding in the segmentation of both interlaminar voidage and dry areas. Furthermore, deep learning improved the ability to detect small voids and was able to accurately segment voids in volumes with less than 2% voidage, whereas thresholding techniques fail in this task. Finally, the application of deep learning to the segmentation of dry areas in micro-CT scans provided sharper results than thresholding, without needing filtering.
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