Imaging atoms and molecules on surfaces by scanning tunnelling microscopy

Chiang, S.

doi:10.1088/0022-3727/44/46/464001

Cited by 8 publications

(4 citation statements)

References 131 publications

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“…SPM methods combined with the corresponding spectroscopy add-ons give information about morphology of the studied objects and the electronic structure down to the atomic scale (figure 2(b)) [23][24][25]. In scanning tunnelling microscopy (STM) the feedback is regulated via setting the value of the tip position above the surface, z, that regulates the tunnelling current, I T , which exponentially depends on z, which gives the distribution of the local density of states at the surface, ρ( ) x y z , , .…”

Section: Scanning Probe Microscopy Methodsmentioning

confidence: 99%

Graphene growth and properties on metal substrates

Dedkov¹,

Voloshina

2015

J. Phys.: Condens. Matter

100

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Graphene-metal interface as one of the interesting graphene-based objects attracts much attention from both application and fundamental science points of view. This paper gives a timely review of the recent experimental works on the growth and the electronic properties of the graphene-metal interfaces. This work makes a link between huge amount of experimental and theoretical data allowing one to understand the influence of the metallic substrate on the electronic properties of a graphene overlayer and how its properties can be modified in a controllable way. The further directions of studies and applications of the graphene-metal interfaces are discussed.

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Section: Scanning Probe Microscopy Methodsmentioning

confidence: 99%

Graphene growth and properties on metal substrates

Dedkov¹,

Voloshina

2015

J. Phys.: Condens. Matter

100

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“…For a review of different approaches in STM and AFM we refer to the more intensive review papers. [29][30][31][32] In the more sophisticated 3D NC-AFM measurements the I T (z) and Df (z) curves are collected on a grid. Then these curves are combined in one data set, which is used for the analysis.…”

Section: Methodsmentioning

confidence: 99%

Multichannel scanning probe microscopy and spectroscopy of graphene moiré structures

Dedkov¹,

Voloshina

2014

Phys. Chem. Chem. Phys.

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The graphene moiré structures on 4d and 5d metals, as they demonstrate both long (moiré) and short (atomic) scale ordered structures, are the ideal systems for the application of scanning probe methods. Taking graphene-Ir(111) as an example, we present the complex studies of this graphene-metal moiré-structure system by means of 3D scanning tunnelling and atomic force microscopy/spectroscopy as well as Kelvin-probe force microscopy. The results clearly demonstrate variation of the moiré and atomic scale contrast as a function of the bias voltage as well as the distance between the scanning probe and the sample, allowing one to discriminate between topographic and electronic contributions in the imaging of a graphene layer on metals. The presented results are compared with the state-of-the-art density functional theory calculations demonstrating excellent agreement between theoretical and experimental data.

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“…The neuronal micro-connectome, which is based on invasive methods of imaging and reconstruction of neuronal bodies (including synapses) from brain sections (see Van Essen et al, 2013 for an extended review), may be the ultimate structural basis of the brain. However, this approach faces many conceptual and technical challenges and so far has only been completed for the small nervous systems of the nematode C. elegans , possessing only 302 neurons (White et al, 1986; Varshney et al, 2011), as well as partly for zebrafish (Friedrich, 2013) and Drosophila (Chiang, 2011).…”

Section: Introductionmentioning

confidence: 99%

Building the Ferretome

Sukhinin

Engel

Manger

et al. 2015

Preprint

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Databases of structural connections of the mammalian brain, such as CoCoMac (cocomac.g-node.org) or BAMS (brancusi.usc.edu), are valuable resources for the analysis of brain connectivity and the modeling of brain dynamics in species such as the non-human primate or the rodent, and have also contributed to the computational modeling of the human brain. Another model species that is widely used in electrophysiological or developmental studies is the ferret; however, no systematic compilation of brain connectivity is currently available for this species. Thus, we have started developing a database of anatomical connections and architectonic features of the ferret brain (the Ferretome, www.ferretome.org). The main goals of this database project are: (1) to assemble structural information on the ferret brain that is currently widely distributed in the literature or in different in-house laboratory databases into a single resource which is open to the scientific community; (2) to try and build an extendable community resource that is beneficial to researchers in neuroinformatics and computational neuroscience, as well as to neuroanatomists, by adding value to their data through algorithms for efficient data representation, analysis and visualization; (3) to create techniques for the representation of quantitative and raw data; and (4) to expand existing database ontologies in order to accommodate further neuroarchitectural information for identifying essential relations between brain structure and connections. The Ferretome database has adapted essential features of the CoCoMac methodology and legacy. In particular, its data model is derived from CoCoMac. It also uses a semantic parcellation of ferret brain regions as well as a logical brain maps transformation algorithm (objective relational transformation, ORT). The database is being developed in MySQL and has been populated with literature reports on tract tracing observations in the ferret brain using a custom-designed web interface that allows efficient and validated simultaneous input and proofreading by multiple curators. The database is also equipped with a web interface for generating output data that was designed with non-computer science specialist users in mind. This interface can be extended to produce connectivity matrices in several formats including a graphical representation superimposed on established ferret brain maps. An important feature of the Ferretome database is the possibility to trace back entries in connectivity matrices to the original studies archived in the system. Currently, the Ferretome contains 50 reports on connections comprising 20 injection reports with more than 150 labeled source and target areas, the majority reflecting connectivity of subcortical nuclei. We hope that the Ferretome database will become a useful resource for neuroinformatics and neural modeling, and will support studies of the ferret brain as well as facilitate advances in comparative studies of mesoscopic brain connectivity.

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Imaging atoms and molecules on surfaces by scanning tunnelling microscopy

Cited by 8 publications

References 131 publications

Graphene growth and properties on metal substrates

Graphene growth and properties on metal substrates

Multichannel scanning probe microscopy and spectroscopy of graphene moiré structures

Building the Ferretome

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