Abstract
This paper proposes an innovative approach to determine the composition of natural rubber (NR) and styrene butadiene rubber (SBR) blends from the analysis of the data provided by the differential scanning calorimetry (DSC) technique. DSC registers are post-processed, based on a multivariate chemometric approach, consisting in the application of the successive projections algorithm (SPA) as variable selection algorithm and a further application of the partial least squares (PLS) regression method and the leave-one-out cross-validation algorithm. Results attained by applying this approach are compared with those obtained from mid-infrared spectroscopy since this last method has been widely applied during the last decades. Experimental results summarized in the paper prove that this fast and cost-effective approach is useful to determine the composition of unknown incoming NR/SBR blends.
Highlights
Polymer materials have achieved a vital position in all branches of science and technology
This paper reports preliminary results of the chemometric analysis applied to Natural rubber (NR)/Styrene-butadiene rubber (SBR) blends
Some differences among samples are appreciated, they do not allow to determine the composition of the NR/SBR blends
Summary
Polymer materials have achieved a vital position in all branches of science and technology. NR is among the most important polymers because of its widespread use and importance in many industrial areas 1 Another advantage is that NR is obtained from a renewable resource, as opposed to the synthetic rubbers. The vulcanization of the elastomer produces profound changes at the molecular level, because of the formation of bridges or cross-links between polymer chains, forming a crosslinked three-dimensional structure. This modification produces important changes in the material since the physical properties are transformed from soft, weak and with high viscosity to exhibit high elasticity, less grip, insolubility and resistant to the premature aging caused by light, heat or other factors
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