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Cited by 269

The DOI matches its Crossref record; 168 of the 168 references it cites were found in a registry or an index.

Cellulose nanocrystal based composites: A review

Open access
Shojaeiarani, Jamileh, Bajwa, Dilpreet S, Chanda, Saptaparni·2021·Composites Part C: Open Access

Abstract

Cellulose nanocrystals (CNC) have received much attention as renewable, biodegradable, nontoxic, and low-cost nanomaterials with some remarkable properties. Desirable engineering properties of CNC include large surface to volume ratio, high tensile strength (~10 GPa), high stiffness (~110–130 GPa), and high flexibility. They can be chemically modified to tailor their properties for high-end engineering and biomedical applications. Despite their outstanding properties, the wide-scale application is lacking due to their surface characteristics and processing challenges. To achieve their full potential safer extraction methods, improved surface modification and functionalization methods and processing techniques are being researched. This review attempts to access methods for characterizing CNC, and CNC composites as well as their emerging new applications as smart materials. The review is a valuable resource for researchers and scientists working in industry or academia to provide an update on the use of CNC materials and their composites in packaging, biomedical, and high-efficiency energy systems.

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Crossref · 10.1016/j.jcomc.2021.100164

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Metadata

Authors
Shojaeiarani, J., Bajwa, D. S., & Chanda, S.
Venue
Composites Part C: Open Access
Publisher
Elsevier BV
Published
2021-07
Volume
5
Pages
100164
ISSN
2666-6820 (ISSN-L)
OpenAlex
W3170240163
Cited by
269
References
168
FWCI
9.68
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Cellulose nanocrystal based composites: A review. https://app.cochat.ai/papers/10.1016/j.jcomc.2021.100164
The paper
Shojaeiarani, J., Bajwa, D. S., & Chanda, S. (2021). Cellulose nanocrystal based composites: A review. Composites Part C: Open Access. https://doi.org/10.1016/j.jcomc.2021.100164

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.