Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 59,
  • Issue 5,
  • pp. 600-610
  • (2005)

Prediction of Ethylene Content in Melt-State Random and Block Polypropylene by Near-Infrared Spectroscopy and Chemometrics: Influence of a Change in Sample Temperature and Its Compensation Method

Not Accessible

Your library or personal account may give you access

Abstract

This paper reports on the influence of a change in sample temperature, and a method for its compensation, for the prediction of ethylene (C<sub>2</sub>) content in melt-state random polypropylene (RPP) and block polypropylene (BPP) by near-infrared (NIR) spectroscopy and chemometrics. Near-infrared (NIR) spectra of RPP in the melt and solid states were measured by a Fourier transform near-infrared (FT-NIR) on-line monitoring system and an FT-NIR laboratory system. There are some significant differences between the solid and melt-state RPP spectra. Moreover, we investigated the predicted values of the C<sub>2</sub> content from the RPP or BPP spectra measured at 190 °C and 250 °C using the calibration model for the C<sub>2</sub> content developed using the RPP or BPP spectra measured at 230 °C. The errors in the predicted values of the C<sub>2</sub> content depend on the pretreatment methods for each calibration model. It was found that multiplicative signal correction (MSC) is very effective in compensating for the influence of the change of temperature for the RPP or BPP samples on the predicted C<sub>2</sub> content. From the suggestion of principal component analysis (PCA) and difference spectrum analysis, we propose a new compensation method for the temperature change that uses the difference spectra between two spectra sets measured at different temperatures. We achieved good results using the difference spectra between the RPP/BPP spectra sets measured at 190 °C and 250 °C after correction and the calibration model developed with the spectra measured at 230 ° C. The comparison between the method using MSC and the proposed method showed that the predicted error in the latter is slightly better than those in the former.

PDF Article
More Like This
Rapid detection of cellulose and hemicellulose contents of corn stover based on near-infrared spectroscopy combined with chemometrics

Na Wang, Longwei Li, Jinming Liu, Jianfei Shi, Yang Lu, Bo Zhang, Yong Sun, and Wenzhe Li
Appl. Opt. 60(15) 4282-4290 (2021)

Nondestructive determination of SSC in an apple by using a portable near-infrared spectroscopy system

Yizhe Zhang, Jipeng Huang, Qiulei Zhang, Jinwei Liu, Yanli Meng, and Yan Yu
Appl. Opt. 61(12) 3419-3428 (2022)

Accurate and rapid detection of soil and fertilizer properties based on visible/near-infrared spectroscopy

Zhidan Lin, Rujing Wang, Yubing Wang, Liusan Wang, Cuiping Lu, Yang Liu, Zhengyong Zhang, and Likai Zhu
Appl. Opt. 57(18) D69-D73 (2018)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.