Nanocomposite technologies can be significantly enhanced through a careful exploration of the effects of agglomerates on mechanical properties. Existing models are either overly simplified (e.g., neglect agglomeration effects) or often require a significant amount of computational resources. In this study, a novel continuum-based model with a statistical approach was developed. The model is based on a modified three-phase Mori–Tanaka model, which accounts for the filler, agglomerate, and matrix regions. Fillers are randomly dispersed in a defined space to predict agglomeration tendency. The proposed model demonstrates good agreement with the experimentally measured elastic moduli of spin-coated cellulose nanocrystal reinforced polyamide-6 films. The techniques and methodologies presented in the study are sufficiently general in that they can be extended to the analyses of various types of polymeric nanocomposite systems.
Cellulose nanocrystals (CNCs) are an ideal reinforcing agent for polymer nanocomposites. CNCs can form hydrogen bonds with polyamide 6 (PA6); however, the direct effects of unmodified CNCs on PA6 morphology and crystal structure have not been fully elucidated. This work investigated the influence of CNCs on the mechanical performance and physicochemical properties of spin-coated CNC−PA6 films through quantitative analysis using techniques that probe multiple length scales. CNCs interacted with PA6 to induce the γ (chiral) allomorph over the α allomorph at low CNC loadings (≤1 wt %) and nucleated a high density of small uniform spherulites, leading to stiffer nanocomposites. Higher loadings caused CNC aggregation and crystalline, non-spherulitic features. Overall, we hypothesize that the reinforcement mechanism of CNCs in PA6 is dominated by morphological changes in the matrix, not percolation. Understanding CNC−polymer interactions and morphology (on films prepared without thermal processing or surface modification of CNCs) offers "design rules" for how to incorporate CNCs into nanocomposites for optimized material performance in various applications, for example, membranes, coatings, and packaging.
Commonly used severe plastic deformation (SPD) methods are suitable for fabrication of bulk nano and ultrafine-grained metals. Drawbacks of these methods include durability of dies, geometrical restrictions and reduced ductility of the products. In this study, two common machining techniques used in manufacturing of orthopaedic components, turning and milling, were applied on 316L stainless steel as surface SPD to refine the surface microstructures of the workpiece. Machining with optimised parameters resulted in substantial grain refinement down to 98 nm on the surfaces. Biological experiments showed up to ∼70% and ∼280% increased bone cell density on milled and turned samples compared to conventionally machined 316L stainless steel at 5 days, which was correlated with nanocrystallisation and nanoroughness of the samples.
Recent demands for high-performance lightweight materials have brought researchers’ attention to various nanoparticles to reinforce polymeric materials. As such, sustainable and stiff cellulose nanocrystals (CNC) have become a popular candidate as nano-reinforcements. While CNC can offer great advantages, such as high mechanical properties and low density, it might agglomerate even in hydrophilic polymers because of its strong affinity to itself (intra and intermolecular hydrogen bonds) which prevents its broader use in industrial applications. This study aims to improve the compatibility between CNC and polyamide 6 (PA6) by a chemical modification that produces a surface polarity drastically different from non-modified CNC. The surface of CNC was rendered by the covalent coupling of stearic acid (SA) to the surface hydroxyl groups to produce stearate modified CNC (CNC SA). The effect of the modification was analyzed for CNC SA reinforced PA6 nanocomposites, and the results are compared to that of non-modified CNC reinforced PA6 samples. The addition of unmodified CNC to PA6 provided a modest improvement while the addition of CNC-SA provided substantial improvement on the modulus and tensile strength of the nanocomposite films.
The stiffness of polymeric materials can be improved dramatically with the addition of nanoparticles. In theory, as the nanoparticle loading in the polymer increases, the nanocomposite becomes stiffer; however, experiments suggest that little or no stiffness improvement is observed beyond an optimal nanoparticle loading. The mismatch between the theoretical and experimental findings, particularly at high particle loadings, needs to be understood for the effective use of nanoparticles. In this respect, we have recently developed an analytical model to close the gap in the literature and predict elastic modulus of nanocomposites. The model is based on a three-phase Mori-Tanaka model coupled with the Monte-Carlo method, and satisfactorily captures the experimental results, even at high nanoparticle loadings. The developed model can also be used to study the effects of agglomeration in nanocomposites. In this paper, we use this model to study the effects of agglomeration and related model parameters on the stiffness of nanocomposites. In particular, the effects of particle orientation, critical distance, dispersion state and agglomerate property, and particle aspect ratio are investigated to demonstrate capabilities of the model and to observe how optimal particle loading changes with respect these parameters. The study shows that the critical distance defining agglomerates and the properties of agglomerates are the key design parameters at high particle loadings. These two parameters rule the optimal elastic modulus with respect to particle loading. The findings will allow researchers to form design curves and successfully predict the elastic moduli of nanocomposites without the exhaustive experimental undertakings.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.