Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 318

The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.

Sensing using localised surface plasmon resonance sensors

Szunerits, Sabine, Boukherroub, Rabah·2012·Chemical Communications

Abstract

The bright colours of noble metal particles have attracted considerable interest since historical times, where they were used as decorative pigments in stained glass windows. More recently, the tuneable optical properties of metal nanoparticles and their addressability via spectroscopic techniques have brought them back into the forefront of fundamental and applied research fields. Much of the recent attention concerning metal nanoparticles such as gold and silver has been their use as small-volume, ultra-sensitive label-free optical sensors. Plasmonic nanoparticles act in this case as transducers that convert changes in the local refractive index into spectral shifts of the localized surface plasmon resonance (LSPR) band. This LSPR-shift assay is a general technique for measuring binding affinities and rates from any molecule that induces a change in the local refractive index around the metallic nanostructures. By attaching molecular recognition elements (chemical or biological ligands) on the nanostructures, specificity and selectivity to the analyte of interest are introduced into the nanosensor. In this review, we will discuss the different methods used to fabricate plasmonic nanosensors. A special emphasis will be given to techniques used to link plasmonic nanostructures to surfaces. While the difference between colorimetric and refractive index sensing approaches will be briefly described, the importance to distinguish between bulk refractive index (RI) sensing and molecular near-field refractive index sensing will be discussed. The recent progress made in the development of novel surface functionalization strategies together with the formation of optically and mechanically stable LSPR sensors will be highlighted.

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 · 10.1039/c2cc33266c

Cites

68 of 68 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 68 references

Cited by

See all 318

Metadata

Authors
Szunerits, S., & Boukherroub, R.
Venue
Chemical Communications
Published
2012
Volume
48
Issue
72
Pages
8999
ISSN
  • 1359-7345 (ISSN-L)
  • 1364-548X
OpenAlex
W2017147837
Cited by
318
References
68
FWCI
11.05
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: Sensing using localised surface plasmon resonance sensors. https://app.cochat.ai/papers/10.1039/c2cc33266c
The paper
Szunerits, S., & Boukherroub, R. (2012). Sensing using localised surface plasmon resonance sensors. Chemical Communications. https://doi.org/10.1039/c2cc33266c

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.