Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Chemometric Methods for Estimating the Strain Hardening Modulus in Polyethylene Resins

Not Accessible

Your library or personal account may give you access

Abstract

The feasibility of using multiway or N-way partial least square (NPLS) methods to estimate physical properties of 1-butene and 1-hexene polyethylene (PE) copolymers directly from multidimensional data obtained from size exclusion chromatography coupled to a Fourier transform infrared detector (SEC FT-IR) was explored. Digital sample sets of horizontal slices (slabs) of two-dimensional data simulating the molecular weight distribution and the corresponding orthogonal FT-IR spectra were correlated to a particular Y-block response using NPLS. The NPLS results were compared to those obtained through separate estimations using various algorithms and exploratory response surface methods. The estimated strain hardening modulus (<Gp>) for bimodal PE-like digital structures could adequately be modeled using both the linear response surface method (RSM) and NPLS. Although different input values were used, the predicted values for <Gp > by NPLS was found to mirror both the analytical results and the expected structural effects obtained using linear RSM models.

© 2018 The Author(s)

PDF Article
More Like This
Adaptive incremental method for strain estimation in phase-sensitive optical coherence elastography

Yulei Bai, Shuyin Cai, Shengli Xie, and Bo Dong
Opt. Express 29(16) 25327-25336 (2021)

Analysis of strain estimation methods in phase-sensitive compression optical coherence elastography

Jiayue Li, Ewelina Pijewska, Qi Fang, Maciej Szkulmowski, and Brendan F. Kennedy
Biomed. Opt. Express 13(4) 2224-2246 (2022)

Supplementary Material (2)

NameDescription
Supplement 1       Supplemental file.
Supplement 2       Supplemental file.

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.