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Single-Molecule Electrochemistry:
Present Status and Outlook

Author(s):

Serge G. Lemay, Shuo Kang, Klaus Mathwig, Pradyumna S. Singh

Journal:

Accounts of Chemical Research

Year:

2013

Volume:

46

Pages

369-377

DOI:

10.1021/ar300169d

Abstract:

A form of electrical signal transduction that has so far remained relatively underdeveloped at the single-molecule level is the direct detection of the charge transferred in electrochemical processes. The reason for this is simple: only a few electrons are transferred per molecule in a typical faradaic reaction, a heterogeneous charge-transfer reaction that occurs at the electrode’s surface. Detecting this tiny amount of charge is impossible using conventional electrochemical instrumentation. A workaround is to use redox cycling, in which the charge transferred is amplified by repeatedly reducing and oxidizing analyte molecules as they randomly diffuse between a pair of electrodes. For this process to be sufficiently efficient, the electrodes must be positioned within less than 100 nm of each other, and the analyte must remain between the electrodes long enough for the measurement to take place. Early efforts focused on tip-based nanoelectrodes, descended from scanning electrochemical microscopy, to create suitable geometries. However, it has been challenging to apply these technologies broadly.

In this Account, we describe our alternative approach based on electrodes embedded in microfabricated nanochannels, so-called nanogap transducers. Microfabrication techniques grant a high level of reproducibility and control over the geometry of the devices, permitting systematic development and characterization. We have employed these devices to demonstrate single-molecule sensitivity. This method shows good agreement with theoretical analysis based on the Brownian motion of discrete molecules, but only once the finite time resolution of the experimental apparatus is taken into account. These results highlight both the random nature of single-molecule signals and the complications that it can introduce in data interpretation. We conclude this Account with a discussion on how scientists can overcome this limitation in the future to create a new experimental platform that can be generally useful for both fundamental studies and analytical applications.

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