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

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, I3/1, as well as the third relative viscous, v3/1, Chebyshev coefficient. The angular frequency dependency comprised non-quadratic scaling in I3/1\ua0with the applied strain amplitude and a sign change in v3/1. 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

Cellulose Nanocrystal Liquid Crystal Phases: Progress and Challenges in Characterization Using Rheology Coupled to Optics, Scattering, and Spectroscopy

Cellulose nanocrystals (CNCs) self-assemble and can be flow-assembled to liquid crystalline orders in a water suspension. The orders range from nano- to macroscale with the contributions of individual crystals, their micron clusters, and macroscopic assemblies. The resulting hierarchies are optically active materials that exhibit iridescence, reflectance, and light transmission. Although these assemblies have the potential for future renewable materials, details about structures on different hierarchical levels that span from the nano- to the macroscale are still not unraveled. Rheological characterization is essential for investigating flow properties; however, bulk material properties make it difficult to capture the various length-scales during assembly of the suspensions, for example, in simple shear flow. Rheometry is combined with other characterization methods to allow direct analysis of the structure development in the individual hierarchical levels. While optical techniques, scattering, and spectroscopy are often used to complement rheological observations, coupling them in situ to allow simultaneous observation is paramount to fully understand the details of CNC assembly from liquid to solid. This Review provides an overview of achievements in the coupled analytics, as well as our current opinion about opportunities to unravel the structural distinctiveness of cellulose nanomaterials

Unexpected microphase transitions in flow towards nematic order of cellulose nanocrystals

Organization of nanoparticles is essential in order to control their light-matter interactions. We present cellulose nanocrystal suspension organization in flow towards a unidirectional state. Visualization of evolving polarization patterns of the cellulose nanocrystal suspensions is combined with steady and oscillatory shear rheology. Elucidation of the chiral nematic mesophase in a continuous process towards unidirectional order enables control of alignment in a suspension precursor for structural films and reveals thus far in situ unrevealed transition states that were not detectable by rheology alone. The coupled analytics enabled the suspensions of interest to be divided into rheological gels and rheological liquid crystal fluids with detailed information on the microtransition phases. Both populations experienced submicron organization and reached macro-scale homogeneity with unidirectional ordering in continued shear. We quantify the time, shear rate, and recovery time after shear to design an optimizing formation process for controlled wet structures as precursors for dry products

Gel point in CNC dispersion from FT Rheology

A non-linear analysis via Fourier-Transform Rheology (FT-Rheology) and Large Ampli- tude Oscillatory Shear (LAOS) of cellulose nanocrystals (CNC) dispersions is presented. Dynamic frequency and strain sweep measure- ments were performed for different CNC con- centrations with various parameters (w , g ). The relevance of nonlinear material rheological pa- rameters on flow-field-CNC interactions are initially investigated. This preliminary analy- sis is mainly formed on the magnitude of the stress response nonlinearities. Dependence of concentration on phase transition in CNC while applying strain was investigated. A comparison between the linear viscoelastic dynamic moduli and nonlinearities a steep increase in nonlinear response around the gel point

A numerical framework for simulation of swirled adhesive application

A numerical framework for simulation of swirled adhesive application along arbitrary robot motions and substrate geometries is pre- sented. The momentum and continuity equa- tions are solved on a Cartesian octree grid using a finite volume discretization. A viscoelastic constitutive model is used to describe the com- plex rheology of the adhesive and is solved us- ing a previously presented Lagrangian-Eulerian method. The flow from the nozzle to the target surface is modelled using experimental data, and a projected injection model is used to add adhesive material in the simulation close to the surface. The two-phase flow of adhesive and air is then simulated. Numerical results are com- pared with experimental data and good agree- ment is found

A Mechanics Based Surface Image Interpretation Method for Multifunctional Nanocomposites

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

Simulation of viscoelastic squeeze flows for adhesive joining applications

A backwards-tracking Lagrangian–Eulerian method is used to simulate planar viscoelastic squeeze flow. The momentum and continuity equations are discretized with the finite volume method and implicit immersed boundary conditions are used to describe objects in the domain. The viscoelastic squeeze flow, which involves moving solid geometry as well as free surface flow, is chosen for its relevance in industrial applications, such as adhesive parts assembly and hemming. The main objectives are to validate the numerical method for such flows and to outline the grid resolution dependence of important flow quantities. The main part of the study is performed with the Oldroyd-B model, for which the grid dependence is assessed over a wide range of Weissenberg numbers. An important conclusion is that the load exerted on the solids can be predicted with reasonable accuracy using a relatively coarse grid. Furthermore, the results are found to be in excellent agreement with theoretical predictions as well as in qualitative resemblance with numerical results from the literature. The effects of different viscoelastic properties are further investigated using the PTT model, revealing a strong influence of shear-thinning for moderate Weissenberg numbers. Finally, a reverse squeeze flow is simulated, highlighting important aspects in the context of adhesive joining applications

A Backwards-Tracking Lagrangian-Eulerian Method for Viscoelastic Two-Fluid Flows

A new Lagrangian–Eulerian method for the simulation of viscoelastic free surface flow is proposed. The approach is developed from a method in which the constitutive equation for viscoelastic stress is solved at Lagrangian nodes, which are convected by the flow, and interpolated to the Eulerian grid with radial basis functions. In the new method, a backwards-tracking methodology is employed, allowing for fixed locations for the Lagrangian nodes to be chosen a priori. The proposed method is also extended to the simulation of viscoelastic free surface flow with the volume of fluid method. No unstructured interpolation or node redistribution is required with the new approach. Furthermore, the total amount of Lagrangian nodes is significantly reduced when compared to the original Lagrangian–Eulerian method. Consequently, the method is more computationally efficient and robust. No additional stabilization technique, such as both-sides diffusion or reformulation of the constitutive equation, is necessary. A validation is performed with the analytic solution for transient and steady planar Poiseuille flow, with excellent results. Furthermore, the proposed method agrees well with numerical data from the literature for the viscoelastic die swell flow of an Oldroyd-B model. The capabilities to simulate viscoelastic free surface flow are also demonstrated through the simulation of a jet buckling case

Graphene-Based Antimicrobial Biomedical Surfaces

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

Computationally efficient viscoelastic flow simulation using a Lagrangian-Eulerian method and GPU-acceleration

A recently proposed Lagrangian-Eulerian method for viscoelastic flow simulation is extended to high performance calculations on the Graphics Processing Unit (GPU). The two most computationally intensive parts of the algorithm are implemented for GPU calculation, namely the integration of the viscoelastic constitutive equation at the Lagrangian nodes and the interpolation of the resulting stresses to the cell centers of the Eulerian grid. In the original CPU method, the constitutive equations are integrated with a second order backward differentiation formula, while with the proposed GPU method the implicit Euler method is used. To allow fair comparison, the latter is also implemented for the CPU. The methods are validated for two flows, a planar Poiseuille flow of an upper-convected Maxwell fluid and flow past a confined cylinder of a four-mode Phan Thien Tanner fluid, with identical results. The calculation times for the methods are compared for a range of grid resolutions and numbers of CPU threads, revealing a significant reduction of the calculation time for the proposed GPU method. As an example, the total simulation time is roughly halved compared to the original CPU method. The integration of the constitutive equation itself is reduced by a factor 50 to 250 and the unstructured stress interpolation by a factor 15 to 60, depending on the number of CPU threads used