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Theory and Application for the Scanning Tunneling Microscope

Jerry Tersoff, +1 more
- 20 Jun 1983 - 
- Vol. 50, Iss: 25, pp 1998-2001
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TLDR
In this article, a theory for vacuum tunneling between a real solid surface and a model probe with a locally spherical tip is presented, applicable to the recently developed "scanning tunneling microscope."
Abstract
A theory is presented for vacuum tunneling between a real solid surface and a model probe with a locally spherical tip, applicable to the recently developed "scanning tunneling microscope." Calculations for 2\ifmmode\times\else\texttimes\fi{}1 and 3\ifmmode\times\else\texttimes\fi{}1 reconstructions of Au(110) are in excellent agreement with recent experimental results, if an effective radius of curvature of 9 \AA{} is assumed for the tip.

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Exploring Ag(111) Substrate for Epitaxially Growing Monolayer Stanene: A First-Principles Study.

TL;DR: The study reveals that Ag(111) surface is an ideal candidate for growing large-area, high-quality monolayer stanene, and the perfect lattice structure of free-standingStanene can be achieved once the epitaxial stanenes monolayers is detached from Ag( 111) surface.
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Superoperator nonequilibrium Green's function theory of many-body systems; applications to charge transfer and transport in open junctions

TL;DR: In this article, a super-operator nonequilibrium Green's functions (SNGF) is proposed for computing the dynamical response and particle exchange statistics of coupled quantum systems.
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Pseudopotential-based studies of electron transport in graphene and graphene nanoribbons

TL;DR: The theoretical understanding of electron transport in graphene and graphene nanoribbons is reviewed, emphasizing the help provided by atomic pseudopotentials in determining not only the band structure but also other fundamental transport parameters such as electron-phonon matrix elements and line-edge roughness scattering.
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Theoretical description of the stm images of alkanes and substituted alkanes adsorbed on graphite

TL;DR: In this article, a model based on perturbation theory has been developed to predict the scanning tunneling microscopy (STM) images of molecules adsorbed on graphite.
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Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study.

TL;DR: In this article, deep learning networks are developed for automated image analysis and recognition of the defects, creating a library of (meta) stable defect configurations, and density functional theory is used to estimate atomically resolved scanning tunneling microscopy signatures of the classified defects from the created library, allowing identification of several defect types across imaging platforms.
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