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Cited by 374

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Measurement of the Elastic Modulus of Single Bacterial Cellulose Fibers Using Atomic Force Microscopy

Guhados, Ganesh, Wan, Wankei, Hutter, Jeffrey L.·2005·Langmuir

Abstract

The ability of the atomic force microscope to measure forces with subnanonewton sensitivity at nanometer-scale lateral resolutions has led to its use in the mechanical characterization of nanomaterials. Recent studies have shown that the atomic force microscope can be used to measure the elastic moduli of suspended fibers by performing a nanoscale three-point bending test, in which the center of the fiber is deflected by a known force. We extend this technique by modeling the deflection measured at several points along a suspended fiber, allowing us to obtain more accurate data, as well as to justify the mechanical model used. As a demonstration, we have measured a value of 78 +/- 17 GPa for Young's modulus of bacterial cellulose fibers with diameters ranging from 35 to 90 nm. This value is considerably higher than previous estimates, obtained by less direct means, of the mechanical strength of individual cellulose fibers.

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Metadata

Authors
Guhados, G., Wan, W., & Hutter, J. L.
Venue
Langmuir
Published
2005-05-27
Volume
21
Issue
14
Pages
6642-6646
ISSN
  • 0743-7463 (ISSN-L)
  • 1520-5827
OpenAlex
W1997861308
Cited by
374
References
27
FWCI
3.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Measurement of the Elastic Modulus of Single Bacterial Cellulose Fibers Using Atomic Force Microscopy. https://app.cochat.ai/papers/10.1021/la0504311
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Guhados, G., Wan, W., & Hutter, J. L. (2005). Measurement of the Elastic Modulus of Single Bacterial Cellulose Fibers Using Atomic Force Microscopy. Langmuir. https://doi.org/10.1021/la0504311

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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.