Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 185

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Bimaterial Microcantilevers as a Hybrid Sensing Platform

Singamaneni, S., LeMieux, M. C., Lang, H. P., Gerber, C., Lam, Y., Zauscher, S., Datskos, P. G., Lavrik, N. V., Jiang, H., Naik, R. R., Bunning, T. J., Tsukruk, V. V.·2008·Advanced Materials

Abstract

Microcantilevers, one of the most common MEMS structures, have been introduced as a novel sensing paradigm nearly a decade ago. Ever since, the technology has emerged to find important applications in chemical, biological and physical sensing areas. Today the technology stands at the verge of providing the next generation of sophisticated sensors (such as artificial nose, artificial tongue) with extremely high sensitivity and miniature size. The article provides an overview of the modes of detection, theory behind the transduction mechanisms, materials employed as active layers, and some of the important applications. Emphasizing the material design aspects, the review underscores the most important findings, current trends, key challenges and future directions of the microcantilever based sensor technology.

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.200701667

Cites

1 of 1 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 1 references

Metadata

Authors
Singamaneni, S., LeMieux, M. C., Lang, H. P., Gerber, C., Lam, Y., Zauscher, S., Datskos, P. G., Lavrik, N. V., Jiang, H., Naik, R. R., Bunning, T. J., & Tsukruk, V. V.
Venue
Advanced Materials
Publisher
Wiley
Published
2008-01-29
Volume
20
Issue
4
Pages
653-680
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W1972869328
Cited by
185
References
1
FWCI
18.23
Type
journal article
Language
en
Open access
closed

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: Bimaterial Microcantilevers as a Hybrid Sensing Platform. https://app.cochat.ai/papers/10.1002/adma.200701667
The paper
Singamaneni, S., LeMieux, M. C., Lang, H. P., Gerber, C., Lam, Y., Zauscher, S., Datskos, P. G., Lavrik, N. V., Jiang, H., Naik, R. R., Bunning, T. J., & Tsukruk, V. V. (2008). Bimaterial Microcantilevers as a Hybrid Sensing Platform. Advanced Materials. https://doi.org/10.1002/adma.200701667

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.