Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 66,
  • Issue 11,
  • pp. 1269-1278
  • (2012)

Multivariate Analysis of Micro-Raman Spectra of Thermoplastic Polyurethane Blends Using Principal Component Analysis and Principal Component Regression

Not Accessible

Your library or personal account may give you access

Abstract

Probing the specific hydrogen-bonding behavior of thermoplastic polyurethane (TPU) blends using vibrational spectroscopies remains the sin qua non for understanding the link between hydrogen-bonding and phase-segregation behavior. However, current literature holds to more traditional univariate approaches when studying the morphologically interesting normal molecular vibrations of TPUs. In the present study, multivariate analysis, including principal component analysis (PCA) and principal component regression (PCR), is used to scrutinize the relevant Raman bands acquired from a binary mixture of analogous TPU copolymer blends. Considering the near identical behavior of selected spectral regions, PCA was capable of isolating linear and nonlinear composition-dependent trends on PC-scores plots. From here, the PC scores, extracted from wavelengths comprising the carbonyl stretching region (1681-1764 cm<sup>?1</sup>), CH<sub>2</sub> deformations (1380-1500 cm<sup>?1</sup>), aromatic stretch from the hard segment (1617 cm<sup>?1</sup>), and amide II mixed band (1540 cm<sup>?1</sup>), were used to explicitly predict the mole fraction of hard segment present in each blend using PCR. Spectral preprocessing, wavelength selection, and variable scaling were major factors in PCR accurately predicting the weight fraction of each copolymer in spite of the clearly evident, blend-specific spectroscopic behavior.

PDF Article
More Like This
Removal of correlated background in a high-order harmonic transient absorption spectra with principal component regression

Davide FaccialĂ , Benjamin W. Toulson, and Oliver Gessner
Opt. Express 29(22) 35135-35148 (2021)

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