Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 502

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Carbon Nanotubes for Electronic and Electrochemical Detection of Biomolecules

Open access
Kim, S. N., Rusling, J. F., Papadimitrakopoulos, F.·2007·Advanced Materials

Abstract

The unique electronic and optical properties of carbon nanotubes, in conjunction with their size and mechanically robust nature, make these nanomaterials crucial to the development of next‐generation biosensing platforms. In this Review, we present recent innovations in carbon nanotube‐assisted biosensing technologies, such as DNA‐hybridization, protein‐binding, antibody‐antigen and aptamers. Following a brief introduction on the diameter‐ and chirality‐derived electronic characteristics of single‐walled carbon nanotubes, the discussion is focused on the two major schemes for electronic biodetection, namely biotransistor‐ and electrochemistry‐based sensors. Key fabrication methodologies are contrasted in light of device operation and performance, along with strategies for amplifying the signal while minimizing nonspecific binding. This Review is concluded with a perspective on future optimization based on array integration as well as exercising a better control in nanotube structure and biomolecular integration.

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 · 10.1002/adma.200700665

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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

Cites

Show all 3 references

Cited by

See all 502

Metadata

Authors
Kim, S. N., Rusling, J. F., & Papadimitrakopoulos, F.
Venue
Advanced Materials
Publisher
Wiley
Published
2007-09-21
Volume
19
Issue
20
Pages
3214-3228
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2161889325
Cited by
502
References
3
FWCI
41.90
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: Carbon Nanotubes for Electronic and Electrochemical Detection of Biomolecules. https://app.cochat.ai/papers/10.1002/adma.200700665
The paper
Kim, S. N., Rusling, J. F., & Papadimitrakopoulos, F. (2007). Carbon Nanotubes for Electronic and Electrochemical Detection of Biomolecules. Advanced Materials. https://doi.org/10.1002/adma.200700665

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.