2021
DOI: 10.1107/s1600576721004222
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Analyses of hierarchical structures in vulcanized SBR rubber by using contrast-variation USANS and SANS

Abstract: The hierarchical structures of poly(styrene-ran-butadiene) (SBR) rubber vulcanized with sulfur in a swollen state were investigated by using the contrast-variation ultra-small-angle neutron scattering (USANS) and small-angle neutron scattering (SANS) techniques. The following three levels of hierarchical structure were found: (i) ZnO clusters surrounded by dense SBR networks of the order of 1000 Å in size, (ii) dense networks of SBR in the size range of 70–100 Å and (iii) a mesh size of the network of the orde… Show more

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Cited by 3 publications
(3 citation statements)
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“…We employed a Lorentz function for S ξ ( q ) in eq expressed by S ξ ( q ) = S ξ , 0 1 + q 2 ξ 2 where S ξ,0 is the prefactor, and ξ is the correlation length of the polymer network. …”
Section: Resultsmentioning
confidence: 99%
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“…We employed a Lorentz function for S ξ ( q ) in eq expressed by S ξ ( q ) = S ξ , 0 1 + q 2 ξ 2 where S ξ,0 is the prefactor, and ξ is the correlation length of the polymer network. …”
Section: Resultsmentioning
confidence: 99%
“…Thus, the contrast between the RA and melt-like regions is enhanced by the difference in the concentration, and we can distinguish between the RA and melt-like regions. Actually, several studies have found similar behaviors in the adsorption layers of nanocomposites. It was elucidated that adsorption layers exist around fillers, the mobility of the polymers in the adsorption layers is reduced by adsorption on the filler surface, and the degree of swelling of the adsorption layers is lower than that of the matrix regions when swollen by the solvent. The studies analyzed the adsorption layers quantitatively by applying the contrast variation small-angle scattering (CV-SAS) method to the swollen state of the nanocomposites. In CV-SAS experiments, we measure the change in scattering profiles with the variety of the scattering length density (SLD) of one component in systems without the structural changes and clarify the spatial distribution of each component in the system.…”
Section: Introductionmentioning
confidence: 98%
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