Chemical structure based prediction of PAN and oxidized PAN fiber density through a non-linear mathematical model

Badii, Khashayar, Church, Jeffrey S., Golkarnarenji, Gelayol, Naebe, Minoo and Khayyam, Hamid 2016, Chemical structure based prediction of PAN and oxidized PAN fiber density through a non-linear mathematical model, Polymer degradation and stability, vol. 131, pp. 53-61, doi: 10.1016/j.polymdegradstab.2016.06.019.

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Title Chemical structure based prediction of PAN and oxidized PAN fiber density through a non-linear mathematical model
Author(s) Badii, Khashayar
Church, Jeffrey S.
Golkarnarenji, Gelayol
Naebe, MinooORCID iD for Naebe, Minoo
Khayyam, Hamid
Journal name Polymer degradation and stability
Volume number 131
Start page 53
End page 61
Total pages 9
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2016-09
ISSN 0141-3910
Keyword(s) FT-IR ATR
oxidized PAN fiber
non-linear mathematical model
cross-validation method
Science & Technology
Physical Sciences
Polymer Science
Summary The production of carbon fiber, particularly the oxidation/stabilization step, is a complex process. In the present study, a non-linear mathematical model has been developed for the prediction of density of polyacrylonitrile (PAN) and oxidized PAN fiber (OPF), as a key physical property for various applications, such as energy and material optimization, modeling, and design of the stabilization process. The model is based on the available functional groups in PAN and OPF. Expected functional groups, including [Formula presented], [Formula presented], –CH2, [Formula presented], and [Formula presented], were identified and quantified through the full deconvolution analysis of Fourier transform infrared attenuated total reflectance (FT-IR ATR) spectra obtained from fibers. These functional groups form the basis of three stabilization rendering parameters, representing the cyclization, dehydrogenation and oxidation reactions that occur during PAN stabilization, and are used as the independent variables of the non-linear predictive model. The k-fold cross validation approach, with k = 10, has been employed to find the coefficients of the model. This model estimates the density of PAN and OPF independent of operational parameters and can be expanded to all operational parameters. Statistical analysis revealed good agreement between the governing model and experiments. The maximum relative error was less than 1% for the present model.
Language eng
DOI 10.1016/j.polymdegradstab.2016.06.019
Field of Research 010301 Numerical Analysis
010201 Approximation Theory and Asymptotic Methods
030101 Analytical Spectrometry
030304 Physical Chemistry of Materials
030505 Physical Organic Chemistry
030606 Structural Chemistry and Spectroscopy
090499 Chemical Engineering not elsewhere classified
091209 Polymers and Plastics
0303 Macromolecular And Materials Chemistry
0904 Chemical Engineering
0912 Materials Engineering
Socio Economic Objective 860699 Industrial Chemicals and Related Products not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Elsevier
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