Physical model for recognition tunneling

被引:27
作者
Krstic, Predrag [1 ]
Ashcroft, Brian [2 ]
Lindsay, Stuart [2 ,3 ,4 ]
机构
[1] SUNY Stony Brook, Inst Adv Computat Sci, Stony Brook, NY 11794 USA
[2] Arizona State Univ, Biodesign Inst, Tempe, AZ 85287 USA
[3] Arizona State Univ, Dept Phys, Tempe, AZ 85287 USA
[4] Arizona State Univ, Dept Chem & Biochem, Tempe, AZ 85287 USA
关键词
recognition tunneling; multiscale dynamics; thermal fluctuations; hydrogen bond; coarse-grain simulations; chemical analysis; support vector machine; DNA NANOTECHNOLOGY; SIMULATIONS; NUCLEOTIDES; ELECTRODE; DYNAMICS; JUNCTION; BASES;
D O I
10.1088/0957-4484/26/8/084001
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
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.
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页数:9
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