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Electron tomography provides a direct link between the Payne effect and the inter-particle spacing of rubber composites.

Staniewicz L, Vaudey T, Degrandcourt C, Couty M, Gaboriaud F, Midgley P - Sci Rep (2014)

Bottom Line: The filler provides mechanical reinforcement and additional wear resistance to the rubber, but it in turn introduces non-linear mechanical behaviour to the material which most likely arises from interactions between the filler particles, mediated by the rubber matrix.While various studies have been made on the bulk mechanical properties and of the filler network structure (both imaging and by simulations), there presently does not exist any work directly linking filler particle spacing and mechanical properties.Simulations of filler network formation using attractive, repulsive and non-interacting potentials were processed using the same method and compared with the experimental data, with the net result being that an attractive inter-particle potential is the most accurate way of modelling styrene-butadiene rubber-silica composite formation.

View Article: PubMed Central - PubMed

Affiliation: Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, United Kingdom.

ABSTRACT
Rubber-filler composites are a key component in the manufacture of tyres. The filler provides mechanical reinforcement and additional wear resistance to the rubber, but it in turn introduces non-linear mechanical behaviour to the material which most likely arises from interactions between the filler particles, mediated by the rubber matrix. While various studies have been made on the bulk mechanical properties and of the filler network structure (both imaging and by simulations), there presently does not exist any work directly linking filler particle spacing and mechanical properties. Here we show that using STEM tomography, aided by a machine learning image analysis procedure, to measure silica particle spacings provides a direct link between the inter-particle spacing and the reduction in shear modulus as a function of strain (the Payne effect), measured using dynamic mechanical analysis. Simulations of filler network formation using attractive, repulsive and non-interacting potentials were processed using the same method and compared with the experimental data, with the net result being that an attractive inter-particle potential is the most accurate way of modelling styrene-butadiene rubber-silica composite formation.

No MeSH data available.


Related in: MedlinePlus

A comparison between experimental results (large squares) and rubber composite simulated under attractive, repulsive and random filler distribution conditions.Continuous lines are fits to an equation of the form , where ϕ is the volume fraction and A is a free parameter. Error bars on the microscopy data are fitting errors when applying the cumulative log-normal distribution to each percolation curve.
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f3: A comparison between experimental results (large squares) and rubber composite simulated under attractive, repulsive and random filler distribution conditions.Continuous lines are fits to an equation of the form , where ϕ is the volume fraction and A is a free parameter. Error bars on the microscopy data are fitting errors when applying the cumulative log-normal distribution to each percolation curve.

Mentions: The variation in the characteristic spacing, λ, can then be examined as a function of filler volume fraction, as shown in Fig. 3. Each experimental point corresponds to a single reconstructed pillar sample and the volume fraction to the measured value in the reconstructed volume. To interpret this curve, we have fitted the data to a simple function derived by Ambrosetti et al through the distribution of non-interacing prolate spheroids33. Ambrosetti and co-workers showed that to a good approximation a critical cutoff distance, δ, analogous to our characteristic spacing, λ can be related to the volume fraction ϕ by where a and b are the major and minor radii of the prolate spheroid. A best-fit curve to the data, shown in Fig. 3, was found with A = 2.75 ± 0.19 (error is the asymptotic standard error in a non-linear least squares fit). The raw data (volume fraction, μ, σ, fitting errors, where eμ = λ) for each pillar is shown in Supplementary Table 1.


Electron tomography provides a direct link between the Payne effect and the inter-particle spacing of rubber composites.

Staniewicz L, Vaudey T, Degrandcourt C, Couty M, Gaboriaud F, Midgley P - Sci Rep (2014)

A comparison between experimental results (large squares) and rubber composite simulated under attractive, repulsive and random filler distribution conditions.Continuous lines are fits to an equation of the form , where ϕ is the volume fraction and A is a free parameter. Error bars on the microscopy data are fitting errors when applying the cumulative log-normal distribution to each percolation curve.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4260230&req=5

f3: A comparison between experimental results (large squares) and rubber composite simulated under attractive, repulsive and random filler distribution conditions.Continuous lines are fits to an equation of the form , where ϕ is the volume fraction and A is a free parameter. Error bars on the microscopy data are fitting errors when applying the cumulative log-normal distribution to each percolation curve.
Mentions: The variation in the characteristic spacing, λ, can then be examined as a function of filler volume fraction, as shown in Fig. 3. Each experimental point corresponds to a single reconstructed pillar sample and the volume fraction to the measured value in the reconstructed volume. To interpret this curve, we have fitted the data to a simple function derived by Ambrosetti et al through the distribution of non-interacing prolate spheroids33. Ambrosetti and co-workers showed that to a good approximation a critical cutoff distance, δ, analogous to our characteristic spacing, λ can be related to the volume fraction ϕ by where a and b are the major and minor radii of the prolate spheroid. A best-fit curve to the data, shown in Fig. 3, was found with A = 2.75 ± 0.19 (error is the asymptotic standard error in a non-linear least squares fit). The raw data (volume fraction, μ, σ, fitting errors, where eμ = λ) for each pillar is shown in Supplementary Table 1.

Bottom Line: The filler provides mechanical reinforcement and additional wear resistance to the rubber, but it in turn introduces non-linear mechanical behaviour to the material which most likely arises from interactions between the filler particles, mediated by the rubber matrix.While various studies have been made on the bulk mechanical properties and of the filler network structure (both imaging and by simulations), there presently does not exist any work directly linking filler particle spacing and mechanical properties.Simulations of filler network formation using attractive, repulsive and non-interacting potentials were processed using the same method and compared with the experimental data, with the net result being that an attractive inter-particle potential is the most accurate way of modelling styrene-butadiene rubber-silica composite formation.

View Article: PubMed Central - PubMed

Affiliation: Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge, CB3 0FS, United Kingdom.

ABSTRACT
Rubber-filler composites are a key component in the manufacture of tyres. The filler provides mechanical reinforcement and additional wear resistance to the rubber, but it in turn introduces non-linear mechanical behaviour to the material which most likely arises from interactions between the filler particles, mediated by the rubber matrix. While various studies have been made on the bulk mechanical properties and of the filler network structure (both imaging and by simulations), there presently does not exist any work directly linking filler particle spacing and mechanical properties. Here we show that using STEM tomography, aided by a machine learning image analysis procedure, to measure silica particle spacings provides a direct link between the inter-particle spacing and the reduction in shear modulus as a function of strain (the Payne effect), measured using dynamic mechanical analysis. Simulations of filler network formation using attractive, repulsive and non-interacting potentials were processed using the same method and compared with the experimental data, with the net result being that an attractive inter-particle potential is the most accurate way of modelling styrene-butadiene rubber-silica composite formation.

No MeSH data available.


Related in: MedlinePlus