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.
Keywords:
Differential Scanning Calorimetry; Partial least squares; Natural rubber; Composition
