The DOI matches its Crossref record.
Protein detection by optical shift of a resonant microcavity
Abstract
We present an optical biosensor with unprecedented sensitivity for detection of unlabeled molecules. Our device uses optical resonances in a dielectric microparticle (whispering gallery modes) as the physical transducing mechanism. The resonances are excited by evanescent coupling to an eroded optical fiber and detected as dips in the light intensity transmitted through the fiber at different wavelengths. Binding of proteins on the microparticle surface is measured from a shift in resonance wavelength. We demonstrate the sensitivity of our device by measuring adsorption of bovine serum albumin and we show its use as a biosensor by detecting streptavidin binding to biotin.
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.
Integrity signals
Registry
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.
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
Vahala, K. J. (2003) · Nature · doi:10.1038/nature01939 · Cited by 4,878
Ultra-high-Q toroid microcavity on a chip
Armani, D. K., Kippenberg, T. J., Spillane, S. M., & Vahala, K. J. (2003) · Nature · doi:10.1038/nature01371 · Cited by 2,214
Recent progress in nanoimprint technology and its applications
Guo, L. J. (2004) · Journal of Physics D: Applied Physics · doi:10.1088/0022-3727/37/11/r01 · Cited by 733
Fundamental limits and non-reciprocal approaches in non-Hermitian quantum sensing
Lau, H.-K., & Clerk, A. A. (2018) · Nature Communications · doi:10.1038/s41467-018-06477-7 · Cited by 380
Optical ring resonators for biochemical and chemical sensing
Sun, Y., & Fan, X. (2011) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-010-4237-z · Cited by 355
Metadata
- Authors
- Vollmer, F., Braun, D., Libchaber, A., Khoshsima, M., Teraoka, I., & Arnold, S.
- Venue
- Applied Physics Letters
- Publisher
- AIP Publishing
- Published
- 2002-05-27
- Volume
- 80
- Issue
- 21
- Pages
- 4057-4059
- ISSN
- 0003-6951 (ISSN-L)
- 1077-3118
- OpenAlex
- W2015665105
- Cited by
- 903
- References
- 0
- FWCI
- 24.54
- 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: Protein detection by optical shift of a resonant microcavity. https://app.cochat.ai/papers/10.1063/1.1482797
- The paper
- Vollmer, F., Braun, D., Libchaber, A., Khoshsima, M., Teraoka, I., & Arnold, S. (2002). Protein detection by optical shift of a resonant microcavity. Applied Physics Letters. https://doi.org/10.1063/1.1482797
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.