Toru Amari

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.

End‐group characterization of homo‐ and copolyesters of cyclohexane‐1,4‐dimethanol

End groups after the thermal degradation of poly(ethylene terephthalate) (PET) and its cyclohexanedimethanol (CHDM) copolymer were characterized with 1 H NMR. Thermally degraded polymers were obtained by heat treatment at 290 °C. For the PET homopolymer, a vinyl end group appeared, which resulted from thermal cis-β-elimination. For the CHDM copolymer, in addition to a vinyl end group, methylcyclohexene and cyclovinylidene end groups originating from CHDM were formed. The assignment of the 1 H NMR spectrum was performed with information from 13 C NMR and gas chromatography-mass spectrometry. The total amounts of unsaturated species measured by NMR were compared with those estimated by bromination titration. There was good agreement between the values obtained by the two methods, indicating that all the major unsaturated species were accounted for. The mechanism of the formation of the unsaturated end groups was investigated. We suggest, on the basis of the NMR measurements, that the methylcyclohexene and cyclovinylidene groups originating from CHDM were formed by thermal cis-β-elimination as for the PET homopolymer.

Polycondensation Reaction of Bis(Hydroxyethylterephthalate)—Self Modeling Curve Resolution Analysis of On-Line ATR/FT-IR Spectra

This study presents a thorough qualitative-quantitative analysis by self-modeling curve resolution (SMCR) methods of ATR/FT-IR spectra of the polycondensation reaction of bis(hydroxyethylterephthalate) (BHET) that yields poly(ethyleneterephthalate) (PET) as a final product. We used five different SMCR methods to extract pure-component spectra and concentration profiles. All the results obtained by these five methods are compared. It is shown that particular attention should be given to the scaling of the data. The spectral profiles of the species are obtained through the pure variables determined. Because of the appearance of negative absorbances, the spectra are subjected to the alternating least-square procedure. Rank analysis of the mean centered data shows that the IR spectra of the system in the reaction vessel are predominantly determined by those of BHET and PET, but that a small amount of ethylene glycol (EG), which was evacuated from the reaction vessel, also contributes to the spectra.

Real-Time Monitoring of the Oligomerization Reaction of Bis(hydroxyethyl terephthalate) by Near-Infrared Spectroscopy and Chemometrics

The initial oligomerization of bis(hydroxyethyl terephthalate), BHET, was monitored in situ by near-infrared (NIR) spectroscopy with a transmission probe. The amount of hydroxyl end groups, which is a function of the degree of oligomerization, and the amount of ethylene glycol (EG) in the reaction solution were successfully predicted by the NIR spectra combined with partial least-squares (PLS) regression using measured values from 1H-NMR. The models for predicting the amounts of the OH end groups and EG were interpreted by plots of regression coefficients. Although the amount of EG was small, it was possible to extract spectral information about EG by use of these loading plots. This study is a sequel to the previous study that used an attenuated total reflection (ATR) infrared (IR) method. In the last part of this paper we compare the present results obtained by NIR spectroscopy with those by ATR-IR spectroscopy.

Chemometric resolution of ATR-IR spectra data for polycondensation reaction of bis(hydroxyethylterephthalate) with a combination of self-modeling curve resolution (SMCR) and local rank analysis

Self-modeling curve resolution (SMCR) methods, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) and alternating least squares (ALS) were used to calculate pure concentration profiles and pure spectra for the two-way spectral data collected during the on-line polycondensation reaction of bis(hydroxyethylterephthalate) with an ATR-FT-IR spectrometer. In order to improve the resolution results, SIMPLISMA was combined with local rank analysis method, fixed size moving window evolving factor analysis (FSMWEFA) to search for selective regions of various components and then look for the purest wavenumber variables in the selective regions. Such combination allows more accurate determination of the number of chemical components in the reaction system and the calculations of more accurate concentration profiles and spectra.