Masahiko Shimoyama

Two-Dimensional Near-Infrared Correlation Spectroscopy Studies on Composition-Dependent Spectral Variations in Ethylene/Vinyl Acetate Copolymers: Assignments of Bands Due to Ethylene Units in Amorphous, Disordered, and Orthorhombic Crystalline Phases

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.

Nondestructive Discrimination of Biological Materials by Near-Infrared Fourier Transform Raman Spectroscopy and Chemometrics: Discrimination among Hard and Soft Ivories of African Elephants and Mammoth Tusks and Prediction of Specific Gravity of the Ivories

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.

Fourier Transform Raman Spectra of Linear Low-Density Polyethylene and Prediction of Their Density by Multivariate Data Analysis

Fourier transform Raman spectra have been measured for pellets of sixteen kinds of linear low-density polyethylene (LLDPE) with short branches and one kind of PE without any branch. Before we tried chemometrics analysis, the Raman spectra of LLDPE were investigated by comparing them with the spectrum of PE in order to explore the effects of the branches on the Raman spectra. Partial least-squares (PLS) regression was applied to the Raman spectra in the 1600–600 cm−1 region after multiplicative scatter correction (MSC) to propose a calibration model that predicts the density of LLDPE. The correlation coefficient was calculated to be 0.968, and the root mean square error of cross validation (RMSECV) was found to be 0.0018 g/cm3. The loadings plot of regression coefficients for the calibration model shows that, not only a sharp upward peak at 1417 cm−1 corresponding to the CH2 bending mode reflecting the crystallinity, but also a broad downward peak near 1308 cm−1 corresponding to the amorphous board band of LLDPE plays a key role in the prediction of their density. The chemometrics study has deepened the analysis of the Raman spectra of LLDPE. For example, the detailed analysis of the principal component weight loadings plots has elucidated the existence of bands due to the CH3 groups of branches and those arising from amorphous parts of LLDPE that are almost missing or hidden by other intense bands. In other words, the chemometrics analysis has enhanced spectral resolution.

Near infrared spectroscopy and chemometrics analysis of linear low-density polyethylene

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 CH3 groups play important roles in the prediction of density.

Discrimination of ethylene/vinyl acetate copolymers with different composition and prediction of the content of vinyl acetate in the copolymers and their melting points by near-infrared spectroscopy and chemometrics

Near-infrared (NIR) diffuse reflectance spectra have been measured by use of a rotating drawer for pellets of 12 kinds of ethylene/vinyl acetate (EVA) copolymers with vinyl acetate (VA, the comonomer) varying in the 7–44 wt % range. They are unambiguously discriminated from one another by a score plot of the principal component analysis (PCA) Factor 1 and 2, based upon the NIR spectra pretreated by multiplicative scatter correction (MSC). Principal component (PC) weight loadings for Factor 1 show that the discrimination relies largely upon bands due to the overtone and combination modes arising from the VA unit. We have found one “outlier” in the score plot and elucidated its spectral characteristics based upon PC weight loadings for Factor 2. Partial least-squares (PLS) regression has been applied to propose calibration models which predict the VA content in EVA. The models have been prepared for three kinds of pretreatment, the first derivative, the second derivative, and MSC; and four kinds of wavelength regions. The NIR spectra in the 1100–2200 nm region after the MSC treatment has given the best correlation coefficient and standard error of prediction (SEP) of 0.998 and 0.70%, respectively. The calibration models, prepared by NIR diffuse reflectance spectroscopy for the pellet samples, are compared with previously reported models by NIR transmission spectroscopy for the flowing molten samples, and with those by Raman spectroscopy for the pellet samples. PLS regression has also allowed us to predict melting points of the copolymers with the correlation coefficient and SEP of 0.997 and 0.78°C, respectively.

Near infrared spectra of pellets and thin films of high-density, low-density and linear low-density polyethylenes and prediction of their physical properties by multivariate data analysis

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.

Non-destructive analysis of the two subspecies of African elephants, mammoth, hippopotamus, and sperm whale ivories by visible and short-wave near infrared spectroscopy and chemometrics

Visible (VIS) and short-wave near infrared (SW-NIR) spectroscopy was used for non-destructive analysis of ivories. VIS-SW-NIR (500-1000 nm) spectra were measured in situ for five kinds of ivories, that is two subspecies of African elephants, mammoth, hippopotamus, and sperm whale. Chemometrics analyses were carried out for the spectral data from 500 to 1000 nm region. The five kinds of ivories were clearly discriminated from each other on the scores plot of two principal components (PCs) obtained by principal component analysis (PCA). It was noteworthy that the ivories of the two subspecies of African elephants were discriminated by the scores of PC 1. The loadings plot for PC 1 showed that the discrimination relies on the intensity changes in bands due to collagenous proteins and water interacting with proteins. It was found that the scores plot of PC 2 is useful to distinguish between the ivories of the two subspecies of African elephants and the other ivories. We also developed a calibration model that predicted the specific gravity of five kinds of ivories from their VIS-SW-NIR spectral data using partial least squares (PLS)-1 regression. The correlation coefficient and root mean square error of cross validation (RMSECV) of this model were 0.960 and 0.037, respectively.

Non-destructive analysis of photo-degradation of poly(methyl methacrylate) by near infrared light-fibre spectroscopy and chemometrics

Photo-degradation of poly(methyl methacrylate) (PMMA) has been analysed in situ by the use of near infrared (NIR) light-fibre spectroscopy. Fourier transform (FT) NIR spectra have been measured for PMMA plates irradiated by a high-pressure mercury lamp (450 W) for 0, 30, 60, 90, 120, 150, 180 and 210 min. Principal component analysis (PCA) has been carried out for the FT-NIR spectra pretreated by multiplicative scatter correction (MSC) or second derivative. A principal component (PC) weight loadings plot of factor 1 shows that the irradiation time is strongly correlated with the band due to the second overtone of the C=O stretching mode. Partial least squares (PLS) regression has enabled us to propose a calibration model which predicts the irradiation time of the PMMA plates, with a correlation coefficient and the mean square error of cross validation (RMSECV) of 0.995 and 7.2 min, respectively.

Nondestructive discrimination of ivories and prediction of their specific gravity by Fourier-transform Raman spectroscopy and chemometrics

Fourier-transform (FF) Raman spectroscopy and chemometrics were used for nondestructive analysis of ivories. The discrimination of five kinds of ivories, two subspecies of African elephant, mammoth, hippopotamus, and sperm whale, was investigated, and a calibration model for predicting their specific gravity was developed. FT-Raman spectra were measured in situ for them and chemometrics analyses were carried out for the 3050-350 cm(-1) region. The five kinds of ivories were clearly discriminated from each other on the scores plots of two or three principal components (PCs) obtained by principal component analysis (PCA). The loadings plot for PC 1 shows that the discrimination relies on the content ratio of organic collagenous protein and inorganic hydroxyapatite of ivories. The loadings plot for PC 2 shows that bands due to the CH3 and CH2 stretching modes of the protein also play a role in the discrimination. Using partial least squares regression (PLSR), we developed a calibration model that predicts the specific gravity of the ivories from the FT-Raman spectra. The correlation coefficient and root mean square error of cross validation (RMSECV) of this model were 0.980 and 0.024, respectively.

Two-dimensional (2D) correlation coefficient analyses of heavily overlapped near-infrared spectra

Two-dimensional (2D) correlation coefficient analysis is employed to classify and characterize spectral variations among heavily overlapped near-infrared spectra of pellets and films of three kinds of polyethylene (PE), high-density (HD), low density (LD), and linear low-density (LLD) polyethylene, and five kinds of ivory signature seals. The sample-sample (SS) 2D correlation maps are used for classification while the wavenumber-wavenumber (WW) 2D correlation maps are used for determining spectral variation among the above materials. Both correlation maps are obtained by multiplying the original data with themselves. It is found that the NIR spectra of pellets and films of HD PE are clearly different from those of LD PE and LLD PE, while the NIR spectra of five kinds of ivory seals yield easily discernable squares in the SS correlation maps. The background variation is thought to be behind the differentiation of the PE samples because the WW correlation maps do not indicate appearance of new bands. The correlation results are compared with those of principal component analysis (PCA). This study is a novel application of 2D correlation coefficient analysis which reveals that a comprehensive description of demanding spectral systems is achievable by utterly simple mathematical means because 2D correlation maps are obtained via a single mathematical operation.