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Cited by 580

The DOI matches its Crossref record; 212 of the 212 references it cites were found in a registry or an index.

Additive manufacturing of natural fiber reinforced polymer composites: Processing and prospects

Balla, Vamsi Krishna, Kate, Kunal H., Satyavolu, Jagannadh, Singh, Paramjot, Tadimeti, Jogi Ganesh Dattatreya·2019·Composites Part B: Engineering

Abstract

Abstract Throughout the world there have been alarming concerns over the use of nonrenewable resources during manufacturing of goods and associated environmental legislations. Therefore, the use of natural materials and fabrication of composites therefrom, particularly, development of natural fiber reinforced polymer composites is gaining significant attention. Although natural fiber reinforced composites (NFRCs) show strong application prospects, various materials and processing related challenges needs to be addressed to achieve long-term stability and performance. In this review, we attempted to provide an overview of different types of natural fibers, their characteristics and properties enabling them to be used as reinforcing agents in different polymers. Then the unique requirement of fiber surface modification to achieve enhanced fiber-matrix bonding is discussed. The article also discusses conventional processing routes and critical issues associated with NFRCs processing. The use of different additive manufacturing (AM) technologies in processing polymer composites is also discussed. At the end, we have critically analyzed the challenges and opportunities associated with AM of NFRCs.

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Crossref · 10.1016/j.compositesb.2019.106956

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Metadata

Authors
Balla, V. K., Kate, K. H., Satyavolu, J., Singh, P., & Tadimeti, J. G. D.
Venue
Composites Part B: Engineering
Publisher
Elsevier BV
Published
2019-10
Volume
174
Pages
106956
ISSN
1359-8368 (ISSN-L)
OpenAlex
W2947686181
Cited by
580
References
212
FWCI
25.58
Type
journal article
Language
en
Open access
closed

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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.