Lattice-Fringe Fingerprinting: Structural identification of nanocrystals by HRTEM

2007 ◽  
Vol 1026 ◽  
Author(s):  
Moeck Peter ◽  
Ruben Bjorge
Keyword(s):  
Structural Information ◽  
Reciprocal Lattice ◽  
Chemical Information ◽  
Fourier Synthesis ◽  
Transmission Electron ◽  
Structure Factors ◽  
Lattice Geometry ◽  
Group A ◽  
Experimental Side ◽  
Novel Method

AbstractA novel method for the structurally identification of a nanocrystal from a single high resolution (HR) transmission electron microscopy (TEM) micrograph is described. Components of this method are demonstrated on both experimental and simulated HRTEM images. On the experimental side, the structural information that can be extracted from a HRTEM image is the projected reciprocal lattice geometry, the plane symmetry group, a few structure factor amplitudes and phases, and an outline of the projected atomic structure to the limited resolution of the HRTEM (via a Fourier synthesis of the structure factors). Searching for this information in a comprehensive database and matching it with high figures of merit to that of candidate structures should allow for highly discriminatory identifications of nanocrystals, even without additional chemical information as obtainable in analytical TEMs.

scholarly journals Pepinsky's Machine: an interactive graphics-based Fourier synthesis program with applications in teaching and research

1999 ◽  
Vol 32 (4) ◽  
pp. 821-823 ◽  
Author(s):  
Nicholas M. Glykos
Keyword(s):  
Electron Density ◽  
Reciprocal Lattice ◽  
Interactive Graphics ◽  
Lattice Plane ◽  
Fourier Synthesis ◽  
Teaching And Research ◽  
Electron Density Function ◽  
Density Maps ◽  
Structure Factors ◽  
Plane Group

A computer program has been developed which, given a set of structure-factor amplitudes for any centrosymmetric plane group, displays the amplitude-weighted reciprocal-lattice plane and allows the user interactively to assign and modify the phases of the structure factors, while observing the effect of these changes on the corresponding electron density function. The program has the added feature of being able to calculate and interactively display the electron density maps corresponding to all phase combinations of a user-defined subset of structure factors. Applications of the program in both crystallographic teaching and research are discussed.

HRTEM of antigorite: The structure as a polysomatic series

1988 ◽  
Vol 46 ◽  
pp. 566-567
Author(s):  
Gerard E. Spinnler ◽  
Max T. Otten
Keyword(s):  
Crystal Structures ◽  
Structural Information ◽  
Structure Refinement ◽  
Structural Data ◽  
Structural Disorder ◽  
Fourier Synthesis ◽  
Flat Plates ◽  
Serpentine Minerals ◽  
Transmission Electron ◽  
Approximate Composition

Antigorite is one of the serpentine minerals, a group of 1:1 layer silicates with the approximate composition of Mg3Si2O5(OH)4. These minerals display an unusual variety of crystal structures even though they are almost identical in composition; chrysotile has an elongated-tube structure, lizardite occurs as flat plates, and antigorite has corrugates layers.The details of the crystal structures of the serpentine minerals are not completely known. Threedimensional structure refinements only exist for one- and two- layer lizardite. For antigorite, the only direct structural information consists of a two-dimensional Fourier synthesis of hOI diffractions. The lack of detailed structural data on these minerals arises from the complexity of the structures as well as the paucity of sufficiently large, well-formed single crystals. In addition, structural disorder is common in these minerals, making structure refinement difficult.High resolution transmission electron microscopy (HRTEM) has been used to study antigorite in order to discriminate among various structural models of antigorite and to characterize its microstructures

Automated Crystallite Orientation and Phase Mapping in a Transmission Electron Microscope

2011 ◽  
Vol 1318 ◽  
Author(s):  
Sergei Rouvimov ◽  
Peter Moeck ◽  
Ines Häusler ◽  
Wolfgang Neumann ◽  
Stavros Nicolopoulos
Keyword(s):  
Electron Microscope ◽  
Transmission Electron Microscope ◽  
Reciprocal Lattice ◽  
Primary Electron ◽  
Primary Electron Beam ◽  
Crystallographic Databases ◽  
Transmission Electron ◽  
Lattice Geometry ◽  
Precession Electron Diffraction ◽  
Automated Technique

ABSTRACTAn automated technique for the mapping of nanocrystal phases and orientations in a transmission electron microscope (TEM) is briefly described. It is primarily based on the projected reciprocal lattice geometry that is extracted automatically from precession electron diffraction (PED) enhanced spot patterns. The required hardware allows for a scanning-precession movement of the primary electron beam on the crystalline sample and can be interfaced to any newer or older mid-voltage TEM. Comprehensive open-access crystallographic databases that may be used in support of this technique are mentioned.

n-AlGaAs/p-GaAs/n-GaN HETEROJUNCTION BIPOLAR TRANSISTOR: THE FIRST TRANSISTOR FORMED VIA WAFER FUSION

2004 ◽  
Vol 14 (01) ◽  
pp. 265-284 ◽  
Author(s):  
SARAH ESTRADA ◽  
EVELYN HU ◽  
UMESH MISHRA
Keyword(s):  
Structural Information ◽  
Bipolar Transistor ◽  
Heterojunction Bipolar Transistor ◽  
Electrical Performance ◽  
Chemical Information ◽  
Wafer Fusion ◽  
Transmission Electron ◽  
Current Voltage

We discuss the first reported device characteristics of a wafer-fused heterojunction bipolar transistor (HBT), demonstrating the potential of wafer fusion for the production of electrically active heterostructures between lattice-mismatched materials. n-GaAs / n-GaN ("n-n") and p-GaAs / n-GaN ("p-n") heterojunctions were successfully fused and processed into current-voltage (I-V) test structures. The fusion and characterization of these simple structures provided insight for the fabrication of the more complicated HBT structures. Initial HBT devices performed with promising dc common-emitter I-V characteristics and Gummel plots. n-n, p-n, and HBT electrical performance was correlated with systematically varied fusion conditions, and with the quality of the fused interface, given both chemical information provided by secondary ion mass spectroscopy (SIMS) and structural information from high resolution transmission electron microscopy (HRTEM) analysis.

Transmission Electron Diffraction Analysis by Computer

1970 ◽  
Vol 28 ◽  
pp. 40-41
Author(s):  
R.A. Ploc ◽  
G.H. Keech
Keyword(s):  
Electron Diffraction ◽  
Input Data ◽  
Reciprocal Lattice ◽  
Computer Programme ◽  
Transmission Electron Diffraction ◽  
Usual Procedure ◽  
Transmission Electron ◽  
Complex Shapes ◽  
Computer Input ◽  
Diffraction Effects

An unambiguous analysis of transmission electron diffraction effects requires two samplings of the reciprocal lattice (RL). However, extracting definitive information from the patterns is difficult even for a general orthorhombic case. The usual procedure has been to deduce the approximate variables controlling the formation of the patterns from qualitative observations. Our present purpose is to illustrate two applications of a computer programme written for the analysis of transmission, selected area diffraction (SAD) patterns; the studies of RL spot shapes and epitaxy.When a specimen contains fine structure the RL spots become complex shapes with extensions in one or more directions. If the number and directions of these extensions can be estimated from an SAD pattern the exact spot shape can be determined by a series of refinements of the computer input data.

Automated electron tomography: from data collection to image processing

1995 ◽  
Vol 53 ◽  
pp. 26-27
Author(s):  
Weiping Liu ◽  
Jennifer Fung ◽  
W.J. de Ruijter ◽  
Hans Chen ◽  
John W. Sedat ◽  
...  
Keyword(s):  
Image Processing ◽  
Data Collection ◽  
Structural Information ◽  
Imaging Technique ◽  
Electron Tomography ◽  
Ccd Camera ◽  
Automated Data Collection ◽  
Full Control ◽  
Transmission Electron ◽  
Amorphous Structures

Electron tomography is a technique where many projections of an object are collected from the transmission electron microscope (TEM), and are then used to reconstruct the object in its entirety, allowing internal structure to be viewed. As vital as is the 3-D structural information and with no other 3-D imaging technique to compete in its resolution range, electron tomography of amorphous structures has been exercised only sporadically over the last ten years. Its general lack of popularity can be attributed to the tediousness of the entire process starting from the data collection, image processing for reconstruction, and extending to the 3-D image analysis. We have been investing effort to automate all aspects of electron tomography. Our systems of data collection and tomographic image processing will be briefly described.To date, we have developed a second generation automated data collection system based on an SGI workstation (Fig. 1) (The previous version used a micro VAX). The computer takes full control of the microscope operations with its graphical menu driven environment. This is made possible by the direct digital recording of images using the CCD camera.

convergent-beam diffraction from surfaces

1987 ◽  
Vol 45 ◽  
pp. 30-33
Author(s):  
J. A. Eades ◽  
A. E. Smith ◽  
D. F. Lynch
Keyword(s):  
Reciprocal Lattice ◽  
Three Dimensional ◽  
Grazing Incidence ◽  
Three Dimensions ◽  
Plane Figure ◽  
Transmission Electron ◽  
Convergent Beam ◽  
Beam Patterns ◽  
Beam Diffraction

It is quite simple (in the transmission electron microscope) to obtain convergent-beam patterns from the surface of a bulk crystal. The beam is focussed onto the surface at near grazing incidence (figure 1) and if the surface is flat the appropriate pattern is obtained in the diffraction plane (figure 2). Such patterns are potentially valuable for the characterization of surfaces just as normal convergent-beam patterns are valuable for the characterization of crystals.There are, however, several important ways in which reflection diffraction from surfaces differs from the more familiar electron diffraction in transmission.GeometryIn reflection diffraction, because of the surface, it is not possible to describe the specimen as periodic in three dimensions, nor is it possible to associate diffraction with a conventional three-dimensional reciprocal lattice.

Structural studies of small amorphous volumes by electron diffraction

1990 ◽  
Vol 48 (4) ◽  
pp. 122-123
Author(s):  
Pierre Moine
Keyword(s):  
Electron Diffraction ◽  
Born Approximation ◽  
Structural Information ◽  
Fundamental Relation ◽  
X Rays ◽  
Structural Studies ◽  
Diffraction Experiment ◽  
Transmission Electron ◽  
Amorphous Structures ◽  
Diffraction Patterns

Qualitatively, amorphous structures can be easily revealed and differentiated from crystalline phases by their Transmission Electron Microscopy (TEM) images and their diffraction patterns (fig.1 and 2) but, for quantitative structural information, electron diffraction pattern intensity analyses are necessary. The parameters describing the structure of an amorphous specimen have been introduced in the context of scattering experiments which have been, so far, the most used techniques to obtain structural information in the form of statistical averages. When only small amorphous volumes (< 1/μm in size or thickness) are available, the much higher scattering of electrons (compared to neutrons or x rays) makes, despite its drawbacks, electron diffraction extremely valuable and often the only feasible technique.In a diffraction experiment, the intensity IN (Q) of a radiation, elastically scattered by N atoms of a sample, is measured and related to the atomic structure, using the fundamental relation (Born approximation) : IN(Q) = |FT[U(r)]|.

scholarly journals A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2111
Author(s):  
Bo-Wei Zhao ◽  
Zhu-Hong You ◽  
Lun Hu ◽  
Zhen-Hao Guo ◽  
Lei Wang ◽  
...  
Keyword(s):  
Drug Target ◽  
Large Scale ◽  
Computational Models ◽  
Structural Information ◽  
Characteristic Curve ◽  
Representation Learning ◽  
Graph Representation ◽  
Convolutional Network ◽  
Novel Method

Identification of drug-target interactions (DTIs) is a significant step in the drug discovery or repositioning process. Compared with the time-consuming and labor-intensive in vivo experimental methods, the computational models can provide high-quality DTI candidates in an instant. In this study, we propose a novel method called LGDTI to predict DTIs based on large-scale graph representation learning. LGDTI can capture the local and global structural information of the graph. Specifically, the first-order neighbor information of nodes can be aggregated by the graph convolutional network (GCN); on the other hand, the high-order neighbor information of nodes can be learned by the graph embedding method called DeepWalk. Finally, the two kinds of feature are fed into the random forest classifier to train and predict potential DTIs. The results show that our method obtained area under the receiver operating characteristic curve (AUROC) of 0.9455 and area under the precision-recall curve (AUPR) of 0.9491 under 5-fold cross-validation. Moreover, we compare the presented method with some existing state-of-the-art methods. These results imply that LGDTI can efficiently and robustly capture undiscovered DTIs. Moreover, the proposed model is expected to bring new inspiration and provide novel perspectives to relevant researchers.

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