The functional form of energy-differential cross sections for carbon using transmission electron energy-loss spectroscopy

1979 ◽  
Vol 50 (8) ◽  
pp. 5105 ◽  
Author(s):  
D. M. Maher ◽  
D. C. Joy ◽  
R. F. Egerton ◽  
P. Mochel
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Cross Sections ◽  
Differential Cross ◽  
Electron Energy Loss Spectroscopy ◽  
Functional Form ◽  
Differential Cross Sections ◽  
Transmission Electron ◽  
Electron Energy Loss

scholarly journals Deconvolution of Overlapping Features in Electron Energy-loss Spectra: Determination of Absolute Differential Cross Sections for Electron-impact Excitation of Electronic States of Molecules

1997 ◽  
Vol 50 (3) ◽  
pp. 525 ◽  
Author(s):  
L. Campbell ◽  
P. J. O. Teubner ◽  
M. J. Brunger ◽  
B. Mojarrabi ◽  
D. C. Cartwright
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Cross Sections ◽  
Differential Cross ◽  
Electronic States ◽  
Impact Excitation ◽  
Spectroscopic Constants ◽  
Differential Cross Sections ◽  
Electron Energy Loss ◽  
Electron Energy Loss Spectra

A set of three computer programs is reported which allow for the deconvolution of overlapping molecular electronic state structure in electron energy-loss spectra, even in highly perturbed systems. This procedure enables extraction of absolute differential cross sections for electron-impact excitation of electronic states of diatomic molecules from electron energy-loss spectra. The first code in the sequence uses the Rydberg–Klein–Rees procedure to generate potential energy curves from spectroscopic constants, and the second calculates Franck–Condon factors by numerical solution of the Schrödinger equation, given the potential energy curves. The third, given these Franck–Condon factors, the previously calculated relevant energies for the vibrational levels of the respective electronic states (relative to the v″ = 0 level of the ground electronic state) and the experimental energy-loss spectra, extracts the differential cross sections for each state. Each program can be run independently, or the three can run in sequence to determine these cross sections from the spectroscopic constants and the experimental energy-loss spectra. The application of these programs to the specific case of electron scattering from nitric oxide (NO) is demonstrated.

Investigation of Switching Mechanism in HfO2-Based Oxide Resistive Memories by In-Situ Transmission Electron Microscopy and Electron Energy Loss Spectroscopy

2017 ◽  
Author(s):  
T. Dewolf ◽  
D. Cooper ◽  
N. Bernier ◽  
V. Delaye ◽  
A. Grenier ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Hafnium Dioxide ◽  
Switching Mechanism ◽  
Transmission Electron ◽  
Electron Energy Loss

Abstract Forming and breaking a nanometer-sized conductive area are commonly accepted as the physical phenomenon involved in the switching mechanism of oxide resistive random access memories (OxRRAM). This study investigates a state-of-the-art OxRRAM device by in-situ transmission electron microscopy (TEM). Combining high spatial resolution obtained with a very small probe scanned over the area of interest of the sample and chemical analyses with electron energy loss spectroscopy, the local chemical state of the device can be compared before and after applying an electrical bias. This in-situ approach allows simultaneous TEM observation and memory cell operation. After the in-situ forming, a filamentary migration of titanium within the dielectric hafnium dioxide layer has been evidenced. This migration may be at the origin of the conductive path responsible for the low and high resistive states of the memory.

Electron Energy-Loss Spectroscopy (EELS) of Fe-Bearing Olivine and Laihunite (an Oxidized Olivine)

2000 ◽  
Vol 6 (S2) ◽  
pp. 208-209
Author(s):  
Huifang Xu ◽  
Pingqiu Fu
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
High Resolution ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Structure Refinement ◽  
Iron Formation ◽  
Transmission Electron ◽  
Electron Energy Loss

Laihunite that has distorted olivine-type structure with ferric and ferrous irons and ordered distribution of vacancies was first discovered in a high-grade metamorphosed banded iron formation (BIF) [1, 2]. The laihunite coexisting with fayalite (Fe-olivine), magnetite, quartz, ferrosilite, garnet and hedenbergite, formed in the process of oxidation of fayalite [2, 3]. The structure refinement of 1-layer laihunite shows P21/b symmetry and ordered distribution of vacancies in half M1 sites of olivine structure [2, 3]. Early high-resolution transmission electron microscopy (HRTEM) study and HRTEM image simulation of the 1-layer laihunite verified the structure refinement [4].Specimens of weakly oxidized fayalite and laihunite containing fayalite islands collected from Xiaolaihe and Menjiagou of Liaoning Province, NE China, have been studied using selected area electron diffraction (SAED), high-resolution transmission electron microscopy (HRTEM), electron energy-loss spectroscopy (EELS), and X-ray energy-dispersive spectroscopy.

Analysis of AlxGa1-xN nanowires through simulated methods of scanning transmission electron microscopy and electron energy-loss spectroscopy

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
R. Kumar ◽  
P.J. Phillips ◽  
R.F. Klie
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Scanning Transmission Electron Microscopy ◽  
Scanning Transmission Electron ◽  
Transmission Electron ◽  
Scanning Transmission ◽  
Electron Energy Loss

AlxGa1-xN nanowires have promising applications in ultraviolet light emitting diodes (LEDs). However, these nanowires are not typical p-n junction semiconductors, but rather rely on varying concentrations of Al versus Ga to produce electron hole pairs. More information on the atomic structure is needed to better understand the properties of these nanowires. In this study, AlxGa1-xN nanowires were imaged using scanning transmission electron microscopy (STEM) and compared to computer simulated STEM images to obtain physical information on the nanowires. Electron energy-loss spectroscopy (EELS) and FEFF9 computer simulations were also performed to better understand the structural and chemical properties of the nanowires. Results from these simulations showed that changes in the chemical ordering of the nanowires were responsible for changes in intensity and resolution in the images. These intensity and resolution trends were not a result of interface effects. This will help to further characterize nanowires in the future.

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