Characterization of Size and Aggregation for Cellulose Nanocrystal Dispersions Separated by Asymmetrical-Flow Field-Flow Fractionation.

Asymmetrical-flow field-flow fractionation Atomic force microscopy Cellulose nanocrystals Transmission electron microscopy

Journal

Cellulose (London, England)
ISSN: 0969-0239
Titre abrégé: Cellulose (Lond)
Pays: England
ID NLM: 101215688

Informations de publication

Date de publication:
2019
Historique:
entrez: 23 11 2020
pubmed: 1 1 2019
medline: 1 1 2019
Statut: ppublish

Résumé

Cellulose nanocrystals (CNCs) derived from various types of cellulose biomass have significant potential for applications that take advantage of their availability from renewable natural resources and their high mechanical strength, biocompatibility and ease of modification. However, their high polydispersity and irregular rod-like shape present challenges for the quantitative dimensional determinations that are required for quality control of CNC production processes. Here we have fractionated a CNC certified reference material using a previously reported asymmetrical-flow field-flow fractionation (AF4) method and characterized selected fractions by atomic force microscopy (AFM) and transmission electron microscopy. This work was aimed at addressing discrepancies in length between fractionated and unfractionated CNC and obtaining less polydisperse samples with fewer aggregates to facilitate microscopy dimensional measurements. The results demonstrate that early fractions obtained from an analytical scale AF4 separation contain predominantly individual CNCs. The number of laterally aggregated "dimers" and clusters containing 3 or more particles increases with increasing fraction number. Size analysis of individual particles by AFM for the early fractions demonstrates that the measured CNC length increases with increasing fraction number, in good agreement with the rod length calculated from the AF4 multi-angle light scattering data. The ability to minimize aggregation and polydispersity for CNC samples has important implications for correlating data from different sizing methods.

Identifiants

pubmed: 33223627
pmc: PMC7676384
mid: NIHMS1613477
pii:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Intramural NIST DOC
ID : 9999-NIST
Pays : United States

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Auteurs

Maohui Chen (M)

National Research Council Canada, Ottawa, ON, K1A 0R6, Canada.

Jeremie Parot (J)

National Institute of Standards and Technology, Gaithersburg, Maryland, 20899-8520, USA.

Arnab Mukherjee (A)

National Institute of Standards and Technology, Gaithersburg, Maryland, 20899-8520, USA.

Martin Couillard (M)

National Research Council Canada, Ottawa, ON, K1A 0R6, Canada.

Shan Zou (S)

National Research Council Canada, Ottawa, ON, K1A 0R6, Canada.

Vincent A Hackley (VA)

National Institute of Standards and Technology, Gaithersburg, Maryland, 20899-8520, USA.

Linda J Johnston (LJ)

National Research Council Canada, Ottawa, ON, K1A 0R6, Canada.

Classifications MeSH