Raman spectra have been measured for pellets of five samples of high-density polyethylene (HDPE), seven samples of low-density polyethylene (LDPE), and six samples of linear low-density polyethylene (LLDPE). The obtained Raman spectra have been compared to find out characteristic Raman bands of HDPE, LDPE, and LLDPE. Principal component analysis (PCA) was applied to the Raman spectra in the 1600 -650 cm Ϫ1 region after multiplicative scatter correction (MSC) to discriminate the Raman spectra of the three different PE species. They are classified into three groups by a score plot of PCA factor 1 vs. 2. HDPE with high density and high crystallinity gives high scores on the factor 1 axis, while LDPE with low density and low crystallinity yields negative scores on the same axis. It seems that factor 1 reflects the density or crystallinity. A PC weight loadings plot for factor 1 shows six upward peaks corresponding to the bands arising from the crystalline parts or all-trans O(CH 2 ) n O groups and seven downward peaks ascribed to the bands of the amorphous or anisotropic regions and those arising from the short branches. Partial least-squares (PLS-1) regression was applied to the Raman spectra after MSC to propose calibration models that predict the density, crystallinity, and melting points of the polyethylenes. The correlation coefficient was calculated to be 0.9941, 0.9800, and 0.9709 for the density, crystallinity, and melting point, respectively, and their root-mean-square error of cross validation (RMSECV) was found to be 0.0015, 3.3707, and 2.3745, respectively. The loadings plot of factor 2 for the prediction of melting point is largely different from those for the prediction of density and crystallinity.

Generalized two-dimensional (2D) correlation spectroscopy has been applied to the study of the composition-dependent near-infrared (NIR) spectral changes in 11 different ethylene/vinyl acetate (EVA) copolymers with vinyl acetate (VA) content from 6 to 42 wt %. The 2D synchronous correlation analysis of the 11 NIR spectra has separated the bands due to ethylene units from those due to the VA units. The obtained results are consistent with those reached by the calculation of the second derivative and by chemometrics analysis reported in our previous paper. However, the 2D correlation analysis has given clearer evidence for the band separation. Two-dimensional asynchronous correlation analysis has revealed out-of-phase variations between some bands due to ethylene and some bands due to VA and has determined the order of intensity change between them. On the basis of the order of intensity change, the bands of ethylene in the orthorhombic crystalline phase have been discriminated from those in the amorphous and disordered phases. This paper discusses the potentials of three powerful techniques, 2D correlation analysis, the calculation of the second derivatives, and that of regression coefficients in chemometrics, in unraveling rather complicated NIR spectra.

Generalized two-dimensional (2D) FT-Raman correlation spectroscopy has been applied to the study of the composition-induced structural changes in eleven different ethylene/vinyl acetate (EVA) copolymers with vinyl acetate (VA) content varying from 6 to 42 wt %. The eleven copolymer samples have been divided into four sets according to their composition range, and 2D correlation analysis has been applied to detect the characteristic bands for each set. Throughout the composition range of EVA copolymers, the increase of VA content always causes the crystalline lamellae to shrink, the amorphous interlamellar layers to expand, the all-trans −(CH2)− n conformers to decrease, and the gauche conformers to increase in population. In particular, for the EVA with 7 wt % VA, small addition of VA comonomers acts as spacers between adjacent methylene segments and converts the orthorhombic unit cell to the anisotropic unit cell, manifested by the correlation splittings at (1438 cm-1, 1415 cm-1) and (1446 cm-1, 1434 cm-1), respectively. For the EVA with 26 wt % VA, small addition of VA comonomers mainly shortens the length of continual methylene segments and shifts the orthorhombic band from 1415 to 1419 cm-1. The 2D correlation analysis has identified the cause-effect relationship for structural events occurring both at the supermolecular phase scale and at the segmental submolecular level.

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Near infrared (NIR) diffuse reflectance spectra have been measured using a rotating drawer for pellets of 16 kinds of linear low-density polyethylene (LLDPE) with short branches and PE without any branches to propose a calibration model which predicts their density and to increase the understanding of NIR spectra of LLDPE. The density of the LLDPE samples investigated was in the range 0.911-0.925 g cm -3 . Partial least squares (PLS) regression has been applied to the original NIR spectra data set, their second derivatives and the spectra after multiplicative scatter correction (MSC) treatment to make up the models. The correlation coefficient was calculated to be 0.961, 0.965 and 0.970 for the original NIR spectra, their second derivatives and those with the MSC treatment, respectively, and the standard error of prediction (SEP) was found to be 0.001 g cm -3 for all the cases. The regression coefficients plot for the calibration models shows that bands at 1192, 1376 and 1698 nm due to the overtone and combination modes of the CH 3 groups play important roles in the prediction of density.

This paper demonstrates the usefulness of near-infrared (NIR) Fourier transform (FT) Raman spectroscopy and chemometrics in nondestructive discrimination of biological materials. The discrimination among three kinds of materials—hard ivories, soft ivories, and mammoth tusks—has been investigated as an example. NIR (1064-nm) excited FT-Raman spectra were measured in situ for these materials, and principal component analysis (PCA) of the obtained spectra was carried out over the 1800–400-cm−1 region. The two kinds of ivories are clearly discriminated from one another on the basis of a one-factor plot. It was found that treatment of the Raman data by multiplicative scatter correction (MSC) greatly improves the ability to discriminate. Principal component weight loadings show that the discrimination relies upon the ratio of collagen and hydroxyapatite included in two kinds of ivories. The discrimination among the hard and soft ivories and mammoth tusks was made by a three-factor plot for FT-Raman spectra after the MSC treatments. Partial least-squares regression (PLSR) enabled us to make a calibration model which predicts the specific gravity of the hard and soft ivories.

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The aim of the present study is to investigate in detail the near infrared (NIR) spectra of the three types of polyethylene, linear low-density polyethylene (LLDPE), low-density polyethylene (LDPE) and high-density polyethylene (HDPE), and to develop calibration models that predict their physical properties such as density, crystallinity and melting point. The effects of spectral resolution on the classification and the prediction of density for the three types of PE have been investigated. Furthermore, the NIR spectral differences among LLDPE, LDPE and HDPE have been explored in more detail using 2 cm -1 resolution. Principal component analysis (PCA) has been performed to differentiate the 18 samples of PE. They are classified into three groups, LLDPE, LDPE and HDPE, by a score plot of the PCA Factor 1 versus 3 based on the NIR spectra pretreated by multiplicative scatter correction (MSC). The 2 cm -1 spectral resolution yields a slightly better result for the classification. Partial least squares (PLS) regression has been applied to the NIR spectra after MSC to propose calibration models that predict the density, crystallinity and melting point of HDPE, LDPE and LLDPE. The correlation coefficient for the density was calculated to be 0.9898, 0.9928, 0.9925 and 0.9872 for the spectra obtained at 2, 4, 8 and 16 cm -1 resolutions, respectively, and the root mean square error of cross validation (RMSECV) was found to be 0.0021, 0.0018, 0.0018 and 0.0023 g cm -3 , respectively. It has been found that the correlation coefficient and RMSECV for the prediction of the density and crystallinity change little with the spectral resolution. However, for the prediction of melting point, the higher resolutions (2 and 4 cm -1 resolution) provide slightly better results than the lower resolutions. NIR transmission spectra of thin films of LLDPE, LDPE and HDPE have also been investigated, and calibration models for predicting their density have been developed for the film spectra.