Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 361

The DOI matches its Crossref record.

Design of Superior Spider Silk: From Nanostructure to Mechanical Properties

Open access
Du, Ning, Liu, Xiang Yang, Narayanan, Janaky, Li, Lian, Lim, Matthew Lek Min, Li, Daiqin·2006·Biophysical Journal

Abstract

Spider dragline silk is of practical interest because of its excellent mechanical properties. However, the structure of this material is still largely unknown. In this article, we report what we believe is a new model of the hierarchical structure of silk based on scanning electron microscope and atomic force microscope images. This hierarchical structure includes beta-sheet, polypeptide chain network, and silk fibril. It turns out that an exceptionally high strength of the spider dragline silk can be obtained by decreasing the size of the crystalline nodes in the polypeptide chain network while increasing the degree of orientation of the crystalline nodes. Based on this understanding, how the reeling speed affects mechanical properties of spider dragline silk can be understood properly. Hopefully, the understanding obtained in this study will shed light on the formation of spider silk, and consequently, on the principles for the design of ultrastrong silk.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1529/biophysj.106.089144

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 361

Metadata

Authors
Du, N., Liu, X. Y., Narayanan, J., Li, L., Lim, M. L. M., & Li, D.
Venue
Biophysical Journal
Publisher
Elsevier BV
Published
2006-12
Volume
91
Issue
12
Pages
4528-4535
ISSN
0006-3495 (ISSN-L)
OpenAlex
W2139737836
Cited by
361
References
0
FWCI
2.79
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Design of Superior Spider Silk: From Nanostructure to Mechanical Properties. https://app.cochat.ai/papers/10.1529/biophysj.106.089144
The paper
Du, N., Liu, X. Y., Narayanan, J., Li, L., Lim, M. L. M., & Li, D. (2006). Design of Superior Spider Silk: From Nanostructure to Mechanical Properties. Biophysical Journal. https://doi.org/10.1529/biophysj.106.089144

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.