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Quantifying Localized Macromolecular Dynamics within Hydrated Cellulose Fibril Aggregates
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Wood Science Center. Beijing Inst Technol, Sch Mat Sci & Engn, Beijing Engn Res Ctr Cellulose & Its Derivat, 5 South Zhongguancun St, Beijing 100081, Peoples R China..
Wageningen Univ & Res, Lab Biophys, Stippeneng 4, NL-6708 WE Wageningen, Netherlands..
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemistry, Applied Physical Chemistry. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Wood Science Center.ORCID iD: 0000-0002-0231-3970
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Wood Science Center.ORCID iD: 0000-0001-5818-2378
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2019 (English)In: Macromolecules, ISSN 0024-9297, E-ISSN 1520-5835, Vol. 52, no 19, p. 7278-7288Article in journal (Refereed) Published
Abstract [en]

Molecular dynamics (MD) simulations of C-13 NMR longitudinal relaxation (T-1) distributions were recently established as a powerful tool for characterizing moisture adsorption in natural amorphous polymers. Here, such computational-experimental synergy is demonstrated in a system with intrinsically high structural heterogeneity, namely crystalline cellulose nanofibrils (CNFs) in highly hydrated aggregated state. In such a system, structure-function properties on the nanoscale remain largely uncovered by experimental means alone. In this work, broadly polydispersed experimental C-13 NMR T-1 distributions could be successfully reproduced in simulations and, for the first time, were decomposed into contributions from distinct molecular sources within the aggregated CNFs, namely, (i) the core and (ii) the less-accessible and accessible surface regions of the CNFs. Furthermore, within the surface groups structurally different sites such as (iii) residues with different hydroxymethyl orientations and (iv) center and origin chains could be discerned based on their distinct molecular dynamics. The MD simulations unravel a direct correlation between dynamical and structural heterogeneity at an atomistic-level resolution that cannot be accessed by NMR experiments. The proposed approach holds the potential to enable quantitative interpretation of NMR data from a range of multicomponent high-performance nanocomposites with significantly heterogeneous macromolecular structure.

Place, publisher, year, edition, pages
AMER CHEMICAL SOC , 2019. Vol. 52, no 19, p. 7278-7288
National Category
Polymer Chemistry
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URN: urn:nbn:se:kth:diva-262947DOI: 10.1021/acs.macromol.9b00472ISI: 000489678400017Scopus ID: 2-s2.0-85072991639OAI: oai:DiVA.org:kth-262947DiVA, id: diva2:1367563
Note

QC 20191104

Available from: 2019-11-04 Created: 2019-11-04 Last updated: 2019-11-04Bibliographically approved

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Chen, PanFuro, IstvanBerglund, LarsWohlert, Jakob

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