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首页> 外文期刊>Journal of near infrared spectroscopy >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
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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

机译：高密度，低密度和线性低密度聚乙烯的粒料和薄膜的近红外光谱以及通过多元数据分析预测其物理性质

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摘要

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{sup}(-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{sup}(-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{sup}(-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{sup}(-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{sup}(-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.
机译：本研究的目的是详细研究三种类型的聚乙烯，线性低密度聚乙烯（LLDPE），低密度聚乙烯（LDPE）和高密度聚乙烯（HDPE）的近红外（NIR）光谱，并开发可预测其物理性质（例如密度，结晶度和熔点）的校准模型。研究了光谱分辨率对三种PE的分类和密度预测的影响。此外，已使用2 cm {sup}（-1）分辨率更详细地探讨了LLDPE，LDPE和HDPE之间的NIR光谱差异。已进行主成分分析（PCA）来区分18个PE样品。根据乘积散射校正（MSC）预处理的NIR光谱，通过PCA因子1对3的得分图将它们分为LLDPE，LDPE和HDPE三类。 2 cm {sup}（-1）的光谱分辨率为分类带来了更好的结果。 MSC之后已将偏最小二乘（PLS）回归应用于NIR光谱，以提供预测HDPE，LDPE和LLDPE的密度，结晶度和熔点的校准模型。对于在2、4、8和16 cm {sup}（-1）分辨率下获得的光谱，密度的相关系数分别为0.9898、0.9928、0.9925和0.9872，以及交叉验证的均方根误差发现（RMSECV）分别为0.0021、0.0018、0.0018和0.0023g cm {sup}（-3）。已经发现，用于预测密度和结晶度的相关系数和RMSECV随光谱分辨率变化很小。但是，对于熔点的预测，较高的分辨率（2和4 cm {sup}（-1）分辨率）比较低的分辨率提供了更好的结果。还研究了LLDPE，LDPE和HDPE薄膜的NIR透射光谱，并针对膜光谱建立了预测其密度的校准模型。

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