Abstract

Recognition tunneling (RT) identifies target molecules trapped between tunneling electrodes functionalized with recognition molecules that serve as specific chemical linkages between the metal electrodes and the trapped target molecule. Possible applications include single molecule DNA and protein sequencing. This paper addresses several fundamental aspects of RT by multiscale theory, applying both all-atom and coarse-grained DNA models: (1) we show that the magnitude of the observed currents are consistent with the results of non-equilibrium Green's function calculations carried out on a solvated all-atom model. (2) Brownian fluctuations in hydrogen bond-lengths lead to current spikes that are similar to what is observed experimentally. (3) The frequency characteristics of these fluctuations can be used to identify the trapped molecules with a machine-learning algorithm, giving a theoretical underpinning to this new method of identifying single molecule signals.

Original languageEnglish (US)
Article number084001
JournalNanotechnology
Volume26
Issue number8
DOIs
StatePublished - Feb 27 2015

Fingerprint

Molecules
DNA
Atoms
Electrodes
Bond length
Green's function
Learning algorithms
Learning systems
Hydrogen bonds
Metals
Proteins

Keywords

  • chemical analysis
  • coarse-grain simulations
  • hydrogen bond
  • multiscale dynamics
  • recognition tunneling
  • support vector machine
  • thermal fluctuations

ASJC Scopus subject areas

  • Bioengineering
  • Chemistry(all)
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Mechanics of Materials
  • Materials Science(all)

Cite this

Physical model for recognition tunneling. / Krstić, Predrag; Ashcroft, Brian; Lindsay, Stuart.

In: Nanotechnology, Vol. 26, No. 8, 084001, 27.02.2015.

Research output: Contribution to journalArticle

Krstić, Predrag ; Ashcroft, Brian ; Lindsay, Stuart. / Physical model for recognition tunneling. In: Nanotechnology. 2015 ; Vol. 26, No. 8.
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