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Quantifying polymer structural component evolution using X-ray scattering and mixed-integer network component analysis

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Title: Quantifying polymer structural component evolution using X-ray scattering and mixed-integer network component analysis
Authors: Tolle, Ian1 tollei@rpi.edu, Martin, Lealon L.1,2,3 lealon@rpi.edu
Source: Computers & Chemical Engineering. Nov2011, Vol. 35 Issue 11, p2564-2578. 15p.
Subjects: Polymers, X-ray scattering, Ethylene, Crystallization, Integer programming, Nonlinear programming, Structural components, Chemometrics
Abstract: Abstract: In this work we present a novel computational approach for the extraction of underlying polymer structural component signatures and corresponding structural evolution through decomposition of multivariate X-ray scattering (SAXS/WAXS) datasets. Without assumptions based on structural geometry, this mixed-integer network component analysis (NCA) methodology generates a reduced set of component scattering signatures and component fraction evolution. Structural models are then assigned to each component based on a generalized expression for scattering from multi-phase materials. The methodology is applied systematically to the study of ethylene/alpha-olefin copolymer isothermal crystallization. The decomposition generates component signatures defining structures of varying extent within the sample but with constant average local structure. For WAXS datasets, these components can be correlated to crystalline and amorphous regions, while for SAXS datasets they can be correlated to ordered and disordered crystalline lamellae. These model choices agree with structures observed in the literature and are confirmed by comparison to reference crystallinity data. [Copyright &y& Elsevier]
Copyright of Computers & Chemical Engineering is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 65440172
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PubType: Academic Journal
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  Data: Quantifying polymer structural component evolution using X-ray scattering and mixed-integer network component analysis
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  Data: <searchLink fieldCode="AR" term="%22Tolle%2C+Ian%22">Tolle, Ian</searchLink><relatesTo>1</relatesTo><i> tollei@rpi.edu</i><br /><searchLink fieldCode="AR" term="%22Martin%2C+Lealon+L%2E%22">Martin, Lealon L.</searchLink><relatesTo>1,2,3</relatesTo><i> lealon@rpi.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Computers+%26+Chemical+Engineering%22">Computers & Chemical Engineering</searchLink>. Nov2011, Vol. 35 Issue 11, p2564-2578. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Polymers%22">Polymers</searchLink><br /><searchLink fieldCode="DE" term="%22X-ray+scattering%22">X-ray scattering</searchLink><br /><searchLink fieldCode="DE" term="%22Ethylene%22">Ethylene</searchLink><br /><searchLink fieldCode="DE" term="%22Crystallization%22">Crystallization</searchLink><br /><searchLink fieldCode="DE" term="%22Integer+programming%22">Integer programming</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+programming%22">Nonlinear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+components%22">Structural components</searchLink><br /><searchLink fieldCode="DE" term="%22Chemometrics%22">Chemometrics</searchLink>
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  Data: Abstract: In this work we present a novel computational approach for the extraction of underlying polymer structural component signatures and corresponding structural evolution through decomposition of multivariate X-ray scattering (SAXS/WAXS) datasets. Without assumptions based on structural geometry, this mixed-integer network component analysis (NCA) methodology generates a reduced set of component scattering signatures and component fraction evolution. Structural models are then assigned to each component based on a generalized expression for scattering from multi-phase materials. The methodology is applied systematically to the study of ethylene/alpha-olefin copolymer isothermal crystallization. The decomposition generates component signatures defining structures of varying extent within the sample but with constant average local structure. For WAXS datasets, these components can be correlated to crystalline and amorphous regions, while for SAXS datasets they can be correlated to ordered and disordered crystalline lamellae. These model choices agree with structures observed in the literature and are confirmed by comparison to reference crystallinity data. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computers & Chemical Engineering is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.compchemeng.2011.03.027
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 2564
    Subjects:
      – SubjectFull: Polymers
        Type: general
      – SubjectFull: X-ray scattering
        Type: general
      – SubjectFull: Ethylene
        Type: general
      – SubjectFull: Crystallization
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      – SubjectFull: Integer programming
        Type: general
      – SubjectFull: Nonlinear programming
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      – SubjectFull: Structural components
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      – SubjectFull: Chemometrics
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              Text: Nov2011
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