Cellulose crystallinity and ordering of hemicelluloses in pine and birch pulps as revealed by solid-state NMR spectroscopic methods View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2003-12

AUTHORS

Tiina Liitiä, Sirkka Liisa Maunu, Bo Hortling, Tarja Tamminen, Osmo Pekkala, Antero Varhimo

ABSTRACT

Solid-state 13C NMR spectroscopy was used to determine the degree of cellulose crystallinity (CrI) in kraft, flow-through kraft and polysulphide–anthraquinone (PS–AQ) pulps of pine and birch containing various amounts of hemicelluloses. The applicability of acid hydrolysis and the purely spectroscopic proton spin-relaxation based spectral edition (PSRE) method to remove the interfering hemicellulose signals prior to the determination of CrI were also compared. For softwood pulps, the spectroscopic removal of hemicelluloses by PSRE was found to be more efficient than the removal of hemicelluloses by acid hydrolysis. In addition to that, the PSRE method also provides information on the associations between cellulose and hemicelluloses. On the basis of the incomplete removal of xylan from the cellulose subspectra by PSRE, the deposition of xylan on cellulose fibrils and therefore an ordered ultrastructure of xylan in birch pulps was suggested. The ordered structure of xylan in birch pulps was also supported by the observed change of xylan conformation after regeneration. Similarly, glucomannan in pine pulps may have an ordered structure. According to the 13C CPMAS measurements conducted after acid hydrolysis, the degree of cellulose crystallinity was found to be slightly lower in birch pulps than in the pine pulps. Any significant differences in cellulose crystallinity were not found between the pulps obtained by the various pulping methods. Only in pine PS–AQ pulp, the degree of cellulose crystallinity may be slightly lower than in the kraft pulps containing less hemicelluloses. More... »

PAGES

307-316

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1027302526861

DOI

http://dx.doi.org/10.1023/a:1027302526861

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040691747


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