Natural rubber (NR) blends are widely used in many industries because of their excellent integrated properties. However, a simple, easily operational, nondestructive, and accurate method for their quantitative analysis remains as a challenge. This has been always an important issue in the related industries, particularly for their daily quality control tests. One main reason is that NR ingredients vary according to their geographical origin and the harvest time, which renders it hard to set up a versatile analytical protocol for all NRs. Another reason is owing to the defects of the established methods themselves as having been revealed in those relying on TGA, Py-GC/MS, FTIR, and ATR-FTIR. In this study, a simple and feasible method based on near infrared spectroscopy combined with chemometric is proposed to solve this problem for the first time. NR/SBR (styrene-butadiene rubber) rubber blend, the most widely used NR blend, is selected as a typical research subject. Spectral calibration region, factor, and several different pretreatment methods are applied on the spectra data to optimize calibration models. The result shows the optimized calibration model provides a good accuracy (0.135 wt %), intraday precision (0.121 wt %) and interday precision (0.132 wt %) for 3 months. V C 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 41423.
The Fe in graphene was determined by inductively coupled plasma optical emission spectroscopy. The effects of digestion temperature, digestion system, analyzing spectral line, RF power, peristaltic pump flow rate, and working gas flow rate on the measurement results were investigated respectively. The results show that the best digestion effect appear when the digestion temperature is 550 °C and the digestion system is 3ml hydrochloric acid combined with 1ml nitric acid. The most stable and reliable test results obtained when the analyzing spectral line is 259.941 nm, the RF power is 1400W, the peristaltic pump flow rate is 50r/min, the atomizing gas flow rate is 0.8L/min, and the auxiliary gas flow rate is 1.0L/min. The detection limit of the measurement result is 0.029mg/L, the relative standard deviation (n=6) is between 2.5% and 3.2%, and the recovery is between 96.3% and 108.2%.
Based on partial least squares, the dimethyl monomethyme content was measured. The original spectroscopy, smooth, first-order differential, second-order differential, multi-scattered correction, standard regular conversion, the main cause of the child were effectively used. The results show that the model performance of 6 main factors established separately, the correction set coefficient and verification set coefficient of correction set is 0.9999 and 0.9991, respectively, and the correlation set prediction standard deviation is 0.00356, respectively. And 0.0178. This optimal model is used to measure the blind sample of modeling. As a result, the deviation of the measurement results is between -0.028% ∼ 0.012%, the average deviation is from 0.014%, the standard deviation is 0.014%, and the relative standard deviation is 2.9%. The result is satisfactory.
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