Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 572

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

Observation of Quantum Tunneling between Two Plasmonic Nanoparticles

Scholl, Jonathan A., García-Etxarri, Aitzol, Koh, Ai Leen, Dionne, Jennifer A.·2013·Nano Letters

Abstract

The plasmon resonances of two closely spaced metallic particles have enabled applications including single-molecule sensing and spectroscopy, novel nanoantennas, molecular rulers, and nonlinear optical devices. In a classical electrodynamic context, the strength of such dimer plasmon resonances increases monotonically as the particle gap size decreases. In contrast, a quantum mechanical framework predicts that electron tunneling will strongly diminish the dimer plasmon strength for subnanometer-scale separations. Here, we directly observe the plasmon resonances of coupled metallic nanoparticles as their gap size is reduced to atomic dimensions. Using the electron beam of a scanning transmission electron microscope (STEM), we manipulate pairs of ~10-nm-diameter spherical silver nanoparticles on a substrate, controlling their convergence and eventual coalescence into a single nanosphere. We simultaneously employ electron energy-loss spectroscopy (EELS) to observe the dynamic plasmonic properties of these dimers before and after particle contact. As separations are reduced from 7 nm, the dominant dipolar peak exhibits a redshift consistent with classical calculations. However, gaps smaller than ~0.5 nm cause this mode to exhibit a reduced intensity consistent with quantum theories that incorporate electron tunneling. As the particles overlap, the bonding dipolar mode disappears and is replaced by a dipolar charge transfer mode. Our dynamic imaging, manipulation, and spectroscopy of nanostructures enables the first full spectral mapping of dimer plasmon evolution and may provide new avenues for in situ nanoassembly and analysis in the quantum regime.

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 · 10.1021/nl304078v

Cites

30 of 30 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

Cited by

See all 572

Metadata

Authors
Scholl, J. A., García-Etxarri, A., Koh, A. L., & Dionne, J. A.
Venue
Nano Letters
Published
2013-01-14
Volume
13
Issue
2
Pages
564-569
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W2314507373
Cited by
572
References
30
FWCI
23.02
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

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.