Polymer nanocomposites exhibit unique effective properties that do not follow conventional effective media approaches. The nanoparticle-polymer interphase has been shown to strongly influence the nanocomposites behavior due o its significant volume when the particles are nano-sized, affording an opportunity to tune the dielectric response of the
resulting nanocomposite. In this study, we investigate the effects of TiO2 nanoparticles on the electrical properties and the charges distribution and transport in polydimethylsiloxane (PDMS) nanocomposites. Impedance spectroscopy shows suppression of interfacial Maxwell-Wagner-Sillars (MWS) polarization accompanied by a reduction in the low
frequency dielectric permittivity and loss at high temperatures in the presence of the TiO2 nanoparticles. Thermally stimulated discharge current measurements confirm that the suppression of the interfacial polarization relaxations happens by redistributing or depleting the charges through the composite and hindering their mobility, potentially resulting in lower electrical conduction and higher breakdown strength. Although the model materials investigated here are TiO2 nanoparticles and Sylgard 184 PDMS, our findings can be extended to other nanoparticulate-filled elastomer composites to design lightweight dielectrics, actuators and sensors with improved capabilities.
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Poisson ratio mismatch drives low-strain reinforcement in elastomeric nanocomposites
Introduction of nanoparticulate additives can dramatically impact elastomer mechanical response, with large enhancements in modulus, toughness, and strength. Despite the societal importance of these effects, their mechanistic origin remains unsettled. Here, using a combination of theory and molecular dynamics simulation, we show that low-strain extensional reinforcement of elastomers is driven by a nanoparticulate-jamming-induced suppression in the composite Poisson ratio. This suppression forces an increase in rubber volume with extensional deformation, effectively converting a portion of the rubber's bulk modulus into an extensional modulus. A theory describing this effect is shown to interrelate the Poisson ratio and modulus across a matrix of simulated elastomeric nanocomposites of varying loading and nanoparticle structure. This model provides a design rule for structured nanoparticulates that maximizes elastomer mechanical response via suppression of the composite Poisson ratio. It also positions elastomeric nanocomposites as having a qualitatively different character than Poisson-ratio-matched plastic nanocomposites, where this mechanism is absent.
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- Award ID(s):
- 1650460
- NSF-PAR ID:
- 10127595
- Date Published:
- Journal Name:
- Soft Matter
- Volume:
- 15
- Issue:
- 4
- ISSN:
- 1744-683X
- Page Range / eLocation ID:
- 656 to 670
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract In this study, we discuss the characterization and quantification of composite microstructures formed by the external field manipulation of high aspect ratio magnetic particles in an elastomeric matrix. In our prior work, we have demonstrated that the simultaneous application of electric and magnetic fields on hard magnetic particles with geometric anisotropy can create a hierarchy of structures at different length scales, which can be used to achieve a wide range of properties. We aim to characterize these hierarchical structures and relate them to final composite properties so we can achieve our ultimate goal of designing a material for a prescribed performance. The complex particle structures are formed during processing by using electric and magnetic fields, and they are then locked-in by curing the polymer matrix around the particles. The model materials used in the study are barium hexaferrite (BHF) particles and polydimethylsiloxane (PDMS) elastomer. BHF was selected for its hard magnetic properties and high geometric anisotropy. PDMS was selected for its good mechanical properties and its tunable curing kinetics. The resulting BHF-PDMS composites are magnetoactive, i.e., they will deform and actuate in response to magnetic fields. In order to investigate the resulting particle orientation, distribution and alignment and to predict the composite’s macro scale properties, we developed techniques to quantify the particle structures.
The general framework we developed allows us to quantify and directly compare the microstructures created within the composites. To identify structures at the different length scales, images of the composite are taken using both optical microscopy and scanning electron microscopy. We then use ImageJ to analyze them and gather data on particle size, location, and orientation angle. The data is then exported to MATLAB, and is used to run a Minimum Spanning Tree Algorithm to classify the particle structures, and von Mises Distributions to quantify the alignment of said structures.
Important findings show 1) the ability to control structure using a combination of external electric, magnetic and thermal fields; 2) that electric fields promote long range order while magnetic fields promote short-range order; and 3) the resulting hierarchical structure greatly influence bulk material properties. Manipulating particles in a composite material is technologically important because changes in microstructure can alter the properties of the bulk material. The multifield processing we investigate here can form the basis for next generation additive manufacturing platforms where desired properties are tailored locally through in-situ hierarchical control of particle arrangements.
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/c8sm02333f
