Single-molecule surface-enhanced Raman spectroscopy with nanowatt excitation

Literature Information

Publication Date 2014-09-19
DOI 10.1039/C4CP03422H
Impact Factor 3.676
Authors

Brendan L. Darby, Pablo G. Etchegoin, Eric C. Le Ru


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Abstract

We demonstrate the possibility of single molecule (SM) detection via surface-enhanced Raman spectroscopy (SERS) in two seemingly challenging and unexpected cases: first with ultra-low excitation powers of the order of nanowatts and second in as-synthesized and not deliberately-aggregated silver colloid solution. The experiments are carried out using the bi-analyte method on a methylated form of Rhodamine 6G and one of its isotopologues excited at 514 nm close to the electronic resonance. This study spectacularly highlights the fact that SM-SERS detection is much more common and easier to achieve than typically thought, in particular in the case of resonance Raman excitation. As a result, SM-SERS detection in such cases should not be viewed as an indication of good SERS substrate performance as sometimes implicitly assumed.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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