3D Dispersion of Spherical Silica Nanoparticles in Polymer Nanocomposites: A Quantitative Study by Electron Tomography

Morphology-dependent resonance enhanced nonlinear photoacoustic effect in nanoparticle suspension: a temporal-spatial model

The morphology-dependent resonances (MDRs) hotspot, ubiquity formed between the pairs of nanoparticles in close vicinity, has garnered considerable recent attention. By extending this phenomenon to pulse-laser irradiated nanoparticle suspension, we demonstrate that such collective optical/thermal enhancement can give rise to the nonlinear photoacoustic (PA) generation. In this study, a temporal-spatial analytical expression is derived to quantitatively describe the nonlinear PA signal generation from nanoparticles, incorporating the Grüneisen increase at the microscopic individual particle level and MRDs enhancement at the macroscopic suspension level. The dependence of PA nonlinearity on the critical contributors, including the laser pulse width, the particle size, and the statistical interparticle spacing, is quantitatively discussed. The theory is well validated with the finite element method (FEM) and experimentally proved with semiconducting polymer nanoparticles (SPN) suspension. This work may pave a new direction towards effective MDR based nonlinear PA contract agent design.

Structural identification of percolation of nanoparticles

We propose a method relying on structural measurements by small-angle scattering to quantitatively follow aggregation of nanoparticles (NPs) in concentrated colloidal assemblies or suspensions up to percolation, regardless of complex structure factors arising due to interactions. As an experimental model system, the dispersion of silica NPs in a styrene-butadiene matrix has been analyzed by small-angle X-ray scattering and transmission electron microscopy (TEM), as a function of particle concentration. A reverse Monte Carlo analysis applied to the NP scattering compared favorably with TEM. By combining it with an aggregate recognition algorithm, series of representative real space structures and aggregation number distribution functions have been determined up to high concentrations, taking into account particle polydispersity. Our analysis demonstrates that the formation of large percolating aggregates on the scale of the simulation box (of linear dimension 1/q_min, here micron-sized) can be mapped onto the macroscopic percolation characterized by rheology. Our method is thus capable of determining aggregate structure in dense NP systems with strong - possibly unknown - interactions visible in scattering. It is hoped to be useful in many other colloidal systems, beyond the case of polymer nanocomposites exemplarily studied here.

THE PAYNE EFFECT: PRIMARILY POLYMER-RELATED OR FILLER-RELATED PHENOMENON?

The hysteretic softening at small dynamic strains (Payne effect)—related to the rolling resistance and viscoelastic losses of tires—was studied as a function of particle size, filler volume fraction, and temperature for carbon black (CB) reinforced uncrosslinked styrene–butadiene rubber (SBR) and a paste-like material composed of CB-filled paraffin oil. The low-strain limit for dynamic storage modulus was found to be remarkably similar for CB-filled oil and the CB-filled SBR. Small-angle X-ray scattering (SAXS) measurements on the simple composites and detailed data analysis confirmed that the aggregate structures and nature of filler branching/networking of carbon black were virtually identical within oil compared to the high molecular weight polymer matrix. The combined dynamic rheology and SAXS results provide clear evidence that the deformation-induced breaking (unjamming) of the filler network—characterized by filler–filler contacts that are percolated throughout the material—is the main cause for the Payne effect. However, the polymer matrix does play a secondary role as demonstrated by a reduction in Payne effect magnitude with increasing temperature for the CB-reinforced rubber, which was not observed to a significant extent for the oil–CB system.

Nanoparticle self-assembly: from interactions in suspension to polymer nanocomposites

Recent experimental results using in particular small-angle scattering to characterize the self-assembly of mainly hard spherical nanoparticles into higher ordered structures ranging from fractal aggregates to ordered assemblies are reviewed. The crucial control of interparticle interactions is discussed, from chemical surface-modification, or the action of additives like depletion agents, to the generation of directional patches and the use of external fields. It is shown how the properties of interparticle interactions have been used to allow inducing and possibly controlling aggregation, opening the road to the generation of colloidal molecules or potentially metamaterials. In the last part, studies of the microstructure of polymer nanocomposites as an application of volume-spanning and stress-carrying aggregates are discussed.

Determination of the local density of polydisperse nanoparticle assemblies

Quantitative characterization of the average structure of dense nanoparticle assemblies and aggregates is a common problem in nanoscience. Small-angle scattering is a suitable technique, but it is usually limited to not too big assemblies due to the limited experimental range, low concentrations to avoid interactions, and monodispersity to keep calculations tractable. In the present paper, a straightforward analysis of the generally available scattered intensity - even for large assemblies, at high concentrations - is detailed, providing information on the local volume fraction of polydisperse particles with hard sphere interactions. It is based on the identical local structure of infinite homogeneous nanoparticle assemblies and their subsets forming finite-sized clusters. This approach is extended to polydispersity, using Monte-Carlo simulations of hard and moderately sticky hard spheres. As a result, a simple relationship between the observed structure factor minimum - termed the correlation hole - and the average local volume fraction κ on the scale of neighboring particles is proposed and validated through independent aggregate simulations. This relationship shall be useful as an efficient tool for the structural analysis of arbitrarily aggregated colloidal systems.

Molecular Dynamics Simulation Study of Polymer Nanocomposites with Controllable Dispersion of Spherical Nanoparticles

Through coarse-grained molecular dynamics simulation, we construct a novel kind of end-linked polymer network by employing dual end-functionalized polymer chains that chemically attach to the surface of nanoparticles (NPs), so that the NPs act as large cross-linkers. We examine the effects of the length and flexibility of polymer chains on the dispersion of NPs, and the effect of the chain length on the stress-strain behavior and the segment orientation during the deformation process. We find that the stress upturn becomes more prominent with the decrease of the chain length, attributed to the limited extensibility of the chain strand connecting two neighboring NPs. In addition, this end-linked polymer nanocomposite (PNC) is shown to have a temperature-dependent stress-strain behavior that is contrary to traditional physically mixed PNCs, whose mechanical properties deteriorate with increasing temperature. This is due to the stability of the dispersion of NPs and higher entropic elasticity at higher temperature for the former, while the latter has poorer interfacial interaction at higher temperature, leading to less reinforcing efficiency. By imposing a dynamic oscillatory shear deformation, we obtain a dynamic hysteresis loop for end-linked and physically mixed dispersions. Interestingly, the end-linked system possesses a much smaller hysteresis loss than does the physically mixed system, with the latter exhibiting a more prominent decrease with increasing temperature, due to less interfacial contact. Our results demonstrate that end-linked PNCs combine attractive static and dynamic mechanical properties and exhibit an unusual response to temperature, which could find potential applications in the future.

Cluster size distribution of spherical nanoparticles in polymer nanocomposites: rheological quantification and evidence of phase separation

Currently, it is a great challenge to characterize the dispersion quality of nanoparticles in nanocomposites through experimental techniques. In this work, we suggest a new rheological method based on the strain rate amplification effect to determine the cluster size distribution in polymer nanocomposites. The dispersion exponents of nanoparticles from this rheological method are in good agreement with the cluster analysis of transmission electron microscope (TEM) images. We also obtain a critical value of the dispersion exponent from the effective specific surface area of clusters, which separates the well-dispersed state and the phase-separated state. Our results indicate that rheology can be used as a convenient and effective structural analysis method to characterize the nanoparticle cluster size distribution in polymer nanocomposites.

Interconnectivity imaged in three dimensions: Nano-particulate silica-hydrogel structure revealed using electron tomography

We have used Electron Tomography (ET) to reveal the detailed three-dimensional structure of particulate hydrogels, a material category common in e.g. controlled release, food science, battery and biomedical applications. A full understanding of the transport properties of these gels requires knowledge about the pore structure and in particular the interconnectivity in three dimensions, since the transport takes the path of lowest resistance. The image series for ET were recorded using High-Angle Annular Dark Field Scanning Transmission Electron Microscopy (HAADF-STEM). We have studied three different particulate silica hydrogels based on primary particles with sizes ranging from 3.6nm to 22nm and with pore-size averages from 18nm to 310nm. Here, we highlight the nanostructure of the particle network and the interpenetrating pore network in two and three dimensions. The interconnectivity and distribution of width of the porous channels were obtained from the three-dimensional tomography studies while they cannot unambiguously be obtained from the two-dimensional data. Using ET, we compared the interconnectivity and accessible pore volume fraction as a function of pore size, based on direct images on the nanoscale of three different hydrogels. From this comparison, it was clear that the finest of the gels differentiated from the other two. Despite the almost identical flow properties of the two finer gels, they showed large differences concerning the accessible pore volume fraction for probes corresponding to their (two-dimensional) mean pore size. Using 2D pore size data, the finest gel provided an accessible pore volume fraction of over 90%, but for the other two gels the equivalent was only 10-20%. However, all the gels provided an accessible pore volume fraction of 30-40% when taking the third dimension into account.