Dispersion In Polymer Nanocomposites Research Articles

In situ synthesis of boron nitride “nanonoodles” based epoxy nanocomposites with enhanced thermal and dielectric properties

AbstractThe development of low loading fraction nanoscale reinforcements that can be used to improve the dielectric and thermal properties of a polymer remains a challenge by the reason of the insurmountable difficulties with exfoliation and dispersion of polymer nanocomposites. Here, we combined noodle‐like boron nitride nanoribbons (BNNRs) with epoxy resin (EP) by a facile in situ synthesis. The hydroxyl and amino on the BNNRs surface can not only improve dispersibility but also conduct the formation of EP with BNNRs by the in situ ring‐opening reaction. The thermal behavior, dielectric properties, and thermal conductivity of BNNRs/EP nanocomposites with different BNNRs contents were investigated. At an extremely low BNNRs loading fraction of 1 wt%, the thermal conductivity of the nanocomposite increased 48%, which is attributed to the long continuous heat conduction path formed by the strong integration of BNNRs and EP. In addition, the electrical breakdown strength increased from 95.58 to 159.17 kV·mm−1 as the BNNRs content increased, while the nanocomposites maintained acceptable dielectric properties. The results indicate the potential for BNNRs as a new class of nanofiller for dielectric polymers.

Synchronization of thermal properties and constituents in Nanocomposite: Manufacturing, characterization, adjustable properties

AbstractThis is critical to maintain better thermal properties, especially thermal conductivity as well as low particle content along with organized particle dispersion in polymer nanocomposites. Thus, this study is designed to develop a nanocomposite containing a constant reinforcing load of binary particles (carbon and alumina) in the binary matrix of polypropylene (PP)/poly ethylene‐co‐vinyl acetate (EVA). The samples were prepared through the melt blending and hot pressing technique. Compared to pure PP/EVA matrix, the nanocomposites showed a shift in Fourier‐transform infrared spectroscopy peak and absorption intensity, which proves better interaction of nanoparticles with the matrix. The Scanning Electron Microscopy analysis showed the nanocomposite having carbon (C) and alumina (A) relative ratio 2:3 offered even structure with better distribution of nanoparticles compared to other nanocomposites. Also, Differential scanning calorimetry and Thermogravimetric analysis revealed that alumina‐rich binary nanoparticles reinforced composites offer an efficient improvement in thermal behavior. Moreover, the nanocomposite containing high alumina relative ratio (C: A = 2:3) gives a sharp shift in thermal conductivity of 1.57 W/m‐k from 1.2 W/m‐k of carbon‐rich nanocomposite (C: A = 3:2) and 0.16 W/m‐k of pure PP/EVA. However, these relative properties emphasize the important role of this nanocomposite as a programmable thermal material.

Control of Particle Dispersion with Autophobic Dewetting in Polymer Nanocomposites

Good particle dispersion in polymer nanocomposites (PNCs) is often hampered by autophobic dewetting where the matrix polymers are expelled from the grafted polymer, generally believed to result in ...

Extreme shear processing for exfoliating organoclay in nanocomposites with incompatible polymers

Twin screw extrusion at speeds exceeding several thousand rotations per minute (RPM) has the potential to provide extreme shear typically required to break up aggregates and provide good dispersion in polymer nanocomposites. In this work, a novel twin screw extruder with ultra-high screw speed capability has been used to compound the polystyrene (PS) with organically modified nanoclay without using any compatibilizer. The rheological properties and the morphology of the nanocomposites were investigated and compared with simulation after compounding. Screw profiles imparting more and less aggressive mixing were compared over a range of screw speeds from 400 to 4000 RPM. Morphological characterization revealed the necessity of intense shear stress for achieving intercalation and exfoliation when chemical interactions between filler and matrix are unfavorable. The nanocomposites exhibited greater elasticity indicating reinforcement up to a critical screw speed for each screw profile, but further increasing the screw speed resulted in significant polymer degradation, and thus lower viscosity and storage modulus. Moreover, based on calculations of the theoretical adhesion force between the organoclay layers and the shear stress imparted through mixing, the optimized screw speed for a specific screw profile was determined that would overcome lamellar adhesion to form exfoliated nanocomposites, while minimizing the effect of degradation. The resulting model could be extended to any well-defined extruder system as well as other agglomerated nanofillers.

Self-Assembly of Block Copolymer Chains To Promote the Dispersion of Nanoparticles in Polymer Nanocomposites.

In this paper we adopt molecular dynamics simulations to study the amphiphilic AB block copolymer (BCP) mediated nanoparticle (NP) dispersion in polymer nanocomposites (PNCs), with the A-block being compatible with the NPs and the B-block being miscible with the polymer matrix. The effects of the number and components of BCP, as well as the interaction strength between A-block and NPs on the spatial organization of NPs, are explored. We find that the increase of the fraction of the A-block brings different dispersion effect to NPs than that of B-block. We also find that the best dispersion state of the NPs occurs in the case of a moderate interaction strength between the A-block and the NPs. Meanwhile, the stress–strain behavior is probed. Our simulation results verify that adopting BCP is an effective way to adjust the dispersion of NPs in the polymer matrix, further to manipulate the mechanical properties.

A pseudo-thermodynamic description of dispersion for nanocomposites

Dispersion in polymer nanocomposites is determined by the kinetics of mixing and chemical affinity. Compounds like reinforcing filler/elastomer blends display some similarity to colloidal solutions in that the filler particles are close to randomly dispersed through processing. It is attractive to apply a pseudo-thermodynamic approach taking advantage of this analogy between the kinetics of mixing for polymer compounds and thermally driven dispersion for colloids. In order to demonstrate this pseudo-thermodynamic approach, two polybutadienes and one polyisoprene were milled with three carbon blacks and two silicas. These samples were examined using small-angle x-ray scattering as a function of filler concentration to determine a pseudo-second order virial coefficient, A2, which is used as an indicator for compatibility of the filler and polymer. It is found that A2 follows the expected behavior with lower values for smaller primary particles indicating that smaller particles are more difficult to mix. A2 is analogous to the excluded volume and long-range interaction potential for non-equilibrated nanocomposites. The measured values of A2 can be used to specify repulsive interaction potentials for coarse grain DPD simulations of filler/elastomer systems. In addition, new methods to quantify the filler percolation threshold and filler mesh size as a function of filler concentration are obtained. The results represent a new approach to understanding and predicting dispersion in polymer nanocomposites based on a thermodynamic analogy.

Polystyrene-Grafted Silica Nanoparticles: Investigating the Molecular Weight Dependence of Glass Transition and Fragility Behavior

Polymer-tethered nanoparticles provide a strategy to improve particle dispersion in polymer nanocomposites and as materials themselves can exhibit self-healing behavior and enhanced mechanical properties. The few studies that previously characterized the glass transition temperature (Tg) behavior of neat polymer-grafted nanoparticles in the absence of a polymer matrix largely focused on average Tg response. We synthesized polystyrene-grafted silica nanoparticles (Si-PS) via ARGET ATRP, achieving the densely grafted state. Using differential scanning calorimetry, we investigated the brush molecular weight (MW) dependence of Tg, Tg breadth, heat capacity jump (ΔCp), and fragility from 12 to 98 kg/mol. Compared with free PS chains of the same MW, brush Tg increases by 1–2 °C, brush Tg breadth remains unchanged within error down to 36 kg/mol and increases by 3–4 °C at brush MWs of 12 and 13 kg/mol, and brush ΔCp and fragility remain unchanged within error down to 52 kg/mol and then decrease with decreasing MW...

Toward the development of a quantitative tool for predicting dispersion of nanocomposites under non-equilibrium processing conditions

Developing process-structure relationships that predict the impact of the filler-matrix interfacial thermodynamics is crucial to nanocomposite design. This work focuses on developing quantitative relationships between the filler-matrix interfacial energy, the processing conditions, and the nanoparticle dispersion in polymer nanocomposites. We use a database of nanocomposites made of polypropylene, polystyrene, and poly(methyl methacrylate) with three different surface-modified silica nanoparticles under controlled processing conditions. The silica surface was modified with three different monofunctional silanes: octyldimethylmethoxysilane, chloropropyldimethylethoxysilane, and aminopropyldimethylethoxysilane. Three descriptors were used to establish the relationship between interfacial energy, processing conditions, and final nanoparticle dispersion. The ratio of the work of adhesion between filler and polymer to the work of adhesion between filler to filler (descriptor: \( W_{\text{PF}} /W_{\text{FF}} \)) and the mixing energy for the production of the nanocomposites (descriptor: Eγ) are used to determine the final dispersion state of the nanoparticles. The dispersion state is described using a descriptor that characterizes the amount of interfacial area from TEM images (descriptor: \( \bar{I}_{\text{filler}} \)). In order to capture the descriptors accurately, the TEM images of the nanocomposites are binarized using a pixel-wise neighbor-dependent Niblack thresholding algorithm. The significance of the microstructural descriptors was ranked using supervised learning and the interfacial area emerged as the most significant descriptor for describing the nanoparticle dispersion. Our results show a stronger dependence of the final dispersion on the interfacial energy than the processing conditions. Nevertheless, for the final dispersion state, both descriptors have to be taken into account. We also introduce a matrix-dependent term to establish a quantitatively non-linear relationship between the processing and microstructure descriptors.

Role of Casting Solvent on Nanoparticle Dispersion in Polymer Nanocomposites

We investigate the influence of casting solvent on the final spatial dispersion of nanoparticles (NPs) in polymer nanocomposites (PNCs). We prepared nanocomposites of bare silica NPs and poly(2-vinylpyridine) (P2VP) by casting from two different solvents—methyl ethyl ketone (MEK) and pyridine—which are theta/good solvents, respectively, for both the polymer and the NPs. In MEK, we show that P2VP strongly adsorbs onto the silica surface to create a temporally stable bound polymer layer. The resulting “hairy” particles are sterically stabilized against agglomeration, and thus good NP dispersion in PNCs is always achieved, independent of P2VP molecular weight, concentration, or NP loading. On the contrary, in pyridine, P2VP does not adsorb on the silica NPs. The phase behavior in this case is thus governed by a subtle balance among electrostatic repulsion, polymer-induced depletion attraction, and the kinetic slowdown of diffusion-limited NP aggregation. While there is little remnant solvent in the dry PNC, ...

Quantification of layered silicate dispersion in polymer nanocomposites

The dispersion of layered silicates strongly influences the performance of polymer/clay nanocomposites, making the ability to assess clay dispersion quantitatively essential to any effective product quality control effort. However, a quantitative description of dispersion that can be related directly to product performance remains a challenge. Here, we propose a methodology for quantifying clay dispersion, based on describing particle length distribution data obtained from transmission electron microscopy (TEM) micrographs with a gamma probability distribution model, γ(α,β), where the parameter α, (which represents the mean number of platelets per particle), and β, (which represents the mean “effective platelet length”), are shown to be related to the degree of dispersion. Published data sets on a wide variety of polymer nanocomposites are then used to establish an explicit quantitative relationship between these parameters and the extent of dispersion. Specifically, we found that dispersion characteristics are captured effectively by a characteristic dispersion parameter, δ, defined along dispersion contours represented by the empirical relation δ = α + 0.05β, where δ < 5 for exfoliated composites, 5 < δ < 6.5 for less exfoliated composites with stacks containing several layers, and δ > 6.5 for intercalated composites. The proposed method is validated experimentally by using it to quantify the dispersion of polymer nanocomposites produced in our laboratory.

Block‐Copolymer‐Mediated Nanoparticle Dispersion and Assembly in Polymer Nanocomposites

A individual nanoparticle (NP) dispersion in polymer nanocomposites has been obtained through the adsorption of PSbP2VP block copolymer (BCP) at the NPs' surface in solution. The adsorbed block increases the minimum inter-NP distance, while the non-adsorbed block has favourable entropy of mixing with the matrix polymer with the same chemical structure. Physical adsorption of BCP provides a simple, robust means of organizing NPs in a chemically unfavourable polymer.

Nanoparticle dispersion in polymer nanocomposites by spin-diffusion-averaged paramagnetic enhanced NMR relaxometry: scaling relations and applications.

Scaling relationships are identified between NMR longitudinal relaxation times and clay dispersion quality in polymer-paramagnetic clay nanocomposites. Derived from a previously published analytical relationship developed from a lamella-based model, the scaling relationships are based on the enhancement of NMR relaxation rates with increasing exfoliation and dispersion homogeneity. The paramagnetic contribution to the NMR relaxation rate is inversely proportional to the square of the clay interparticle spacing, and directly proportional to the square of the clay weight fraction. These scaling relationships allow the prediction of relative exfoliation of clay particles for a given series of polymer-clay nanocomposites. With independent knowledge of clay exfoliation in a single sample (e.g., from transmission electron microscopy), NMR relaxometry data may be converted into absolute measures of exfoliation. These scaling relations are confirmed with samples of fully exfoliated poly(vinyl alcohol)-montmorillonite nanocomposites, and then used to reveal exfoliation and dispersion quality in a series of nylon-6-montmorillonite nanocomposites. This characterization route is advantageous because NMR relaxometry can more rapidly provide clay dispersion information that is averaged over larger sample volumes than transmission electron microscopy.

Nanoparticle dispersion in polymer nanocomposites by spin-diffusion-averaged paramagnetic enhanced NMR relaxometry

We developed an analytical relationship between nuclear magnetic relaxation and interparticle spacings in polymer nanocomposites filled with paramagnetic-impurity-containing clay nanoparticles. Using (1)H NMR relaxometry, clay nanoparticle dispersion was quantified and agrees with interparticle spacing distributions determined from statistical analysis of TEM images. Some information on the overall quality of clay dispersion is revealed. This work offers a new approach and new insights into nanoparticle dispersion in polymer nanocomposites.

3D Characterization of Nanoparticle Dispersion in Polymer Nanocomposites by TEM Tomography

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.

Revealing the Interface in Polymer Nanocomposites

The morphological characterization of polymer nanocomposites over multiple length scales is a fundamental challenge. Here, we report a technique for high-throughput monitoring of interface and dispersion in polymer nanocomposites based on Förster resonance energy transfer (FRET). Nanofibrillated cellulose (NFC), fluorescently labeled with 5-(4,6-dichlorotriazinyl)-aminofluorescein (FL) and dispersed into polyethylene (PE) doped with Coumarin 30 (C30), is used as a model system to assess the ability of FRET to evaluate the effect of processing on NFC dispersion in PE. The level of energy transfer and its standard deviation, measured by fluorescence spectroscopy and laser scanning confocal microscopy (LSCM), are exploited to monitor the extent of interface formation and composite homogeneity, respectively. FRET algorithms are used to generate color-coded images for a real-space observation of energy transfer efficiency. These images reveal interface formation at a nanoscale while probing a macroscale area that is large enough to be representative of the entire sample. The unique ability of this technique to simultaneously provide orientation/spatial information at a macroscale and nanoscale features, encoded in the FRET signal, provides a new powerful tool for structure-property-processing investigation in polymer nanocomposites.

The quantitative analysis of nano-clay dispersion in polymer nanocomposites by small angle X-ray scattering combined with electron microscopy

The main objective of this work is to propose a new approach for the quantitative analysis of the degree of dispersion of clay particles in the polymer matrix by small angle X-ray scattering (SAXS) combined with electron microscopy. Due to the low temperature processibility and good thermal stability, poly[(butylene succinate)- co-adipate] (PBSA) was chosen as a model polymer matrix for this study. The nanocomposites of PBSA with four different weight percentages of organically modified montmorillonite (OMMT) loadings were prepared via melt-blending method. The dispersed structure of the clay particles in the PBSA matrix was studied by SAXS. Results show that the clay particles are nicely dispersed in the case of all nanocomposites. However, with a systematic increase in clay loading, the dispersed clay structure of the nanocomposites changes from a highly delaminated to a flocculated and then to a stacked intercalated one. The probability of finding neighboring clay particles in the PBSA matrix as well as their thickness was calculated using the Generalized Indirect Fourier Transformation technique developed by Glatter and the modified Caillé theory proposed by Zhang. The morphology of the nanocomposites was also extensively studied by scanning transmission electron microscopy (STEM). In the case of all nanocomposites, SAXS results were in good agreement with STEM observations. Finally, a correlation between the predicted morphology of nanocomposites and their melt-state rheological properties is reported.

Assessing organo‐clay dispersion in polymer nanocomposites

AbstractOrgano‐clay polymer nanocomposites offer improved material properties at very low filler loadings making them of immediate interest for application in body panels, claddings, and instrument panels. This improvement in properties requires that the organo‐clay be well dispersed if not completely exfoliated. Conventionally, the dispersion and exfoliation of the organo‐clay is evaluated using transmission electron microscopy (TEM) and X‐ray diffraction (XRD). Although both TEM and XRD data were found to correlate with flexural modulus of thermoplastic olefin nanocomposite materials, only TEM proved successful in quantifying the dispersion of the organo‐clay in all nanocomposite materials (exfoliated, tactoid, or agglomerated tactoid). XRD was found to be capable of detecting exfoliation and intercalation but is limited because of clay dilution, preferred orientation, mixed‐layering, and other peak broadening factors. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 1110–1117, 2004