Distribution of tunnelling times for quantum electron transport
Creators
- 1. College of Science, Technology and Engineering, James Cook University, Townsville, QLD 4811 (Australia)
Description
In electron transport, the tunnelling time is the time taken for an electron to tunnel out of a system after it has tunnelled in. We define the tunnelling time distribution for quantum processes in a dissipative environment and develop a practical approach for calculating it, where the environment is described by the general Markovian master equation. We illustrate the theory by using the rate equation to compute the tunnelling time distribution for electron transport through a molecular junction. The tunnelling time distribution is exponential, which indicates that Markovian quantum tunnelling is a Poissonian statistical process. The tunnelling time distribution is used not only to study the quantum statistics of tunnelling along the average electric current but also to analyse extreme quantum events where an electron jumps against the applied voltage bias. The average tunnelling time shows distinctly different temperature dependence for p- and n-type molecular junctions and therefore provides a sensitive tool to probe the alignment of molecular orbitals relative to the electrode Fermi energy.
Additional details
Identifiers
- DOI
- 10.1063/1.4944493;
- arXiv
- arXiv:1602.00882v1;
Publishing Information
- Journal Title
- Journal of Chemical Physics
- Journal Volume
- 144
- Journal Issue
- 12
- Journal Page Range
- p. 124105-124105.7
- ISSN
- 0021-9606
- CODEN
- JCPSA6
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 49002946
- Subject category
- S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY;
- Descriptors DEI
- ELECTRIC CURRENTS; ELECTRIC POTENTIAL; ELECTRON TRANSFER; ELECTRONS; MARKOV PROCESS; REACTION KINETICS; TEMPERATURE DEPENDENCE; TUNNEL EFFECT
- Descriptors DEC
- CURRENTS; ELEMENTARY PARTICLES; FERMIONS; KINETICS; LEPTONS; STOCHASTIC PROCESSES
Optional Information
- Notes
- (c) 2016 AIP Publishing LLC