A revised solid-state NMR method to assess the crystallinity of cellulose
Journal article, 2019

The crystallinity of cellulose has a strong impact on various material properties. Over the years, many methods have become available to estimate the crystallinity. The purpose of this work was to revise existing NMR-based methods and to introduce a complementary NMR method related to the 13C T1 relaxation time. The 13C T1 differs by an order of magnitude for amorphous and crystalline polymers among them cellulose. We have utilized the signal boost of 1H–13C cross polarization and the difference in 13C T1 as a filter to calculate the degree of crystallinity. The evaluation of the method is based on the difference in peak integrals, which is fed into a simple equation. The method was applied to five cellulosic samples of different nature and compared the obtained degree of crystallinity with the degree estimated from deconvoluted X-ray scattering patterns. Furthermore, an attempt has been made to give a basic understanding on the origin of CP enhancement in order to validate various proposed NMR methods. With the recent progress of NMR equipment, the presented method can be automatized and applied to a series of samples using a sample changer.

13 C NMR

MAS

Cross-polarization

13 C T 1

Crystallinity

Cellulose

Author

T. Sparrman

Umeå University

Leo Svenningsson

Chalmers, Chemistry and Chemical Engineering, Applied Chemistry, Lars Nordstierna Group

Karin Sjövold

Chalmers, Chemistry and Chemical Engineering, Chemistry and Biochemistry, Physical Chemistry

Wallenberg Wood Science Center (WWSC)

Lars Nordstierna

Chalmers, Chemistry and Chemical Engineering, Applied Chemistry, Lars Nordstierna Group

Gunnar Westman

Chalmers, Chemistry and Chemical Engineering, Chemistry and Biochemistry

Diana Bernin

University of Gothenburg

Chalmers, Chemistry and Chemical Engineering, Chemical Technology, Chemical Engineering Design

Cellulose

0969-0239 (ISSN)

Vol. 26 17 8993-9003

Subject Categories

Polymer Technologies

Textile, Rubber and Polymeric Materials

Probability Theory and Statistics

DOI

10.1007/s10570-019-02718-0

More information

Latest update

11/12/2019