Subcellular localization of cadmium in the root cells ofAllium cepa by electron energy loss spectroscopy and cytochemistry

2004 ◽  
Vol 29 (3) ◽  
pp. 329-335 ◽  
Author(s):  
Donghua Liu ◽  
Ingrid Kottke
Keyword(s):  
Subcellular Localization ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Root Cells ◽  
Ofallium Cepa ◽  
Electron Energy Loss

Subcellular Localization of Fluorinated Serotonin in Human Platelets by Electron Energy-Loss Spectroscopy

1977 ◽  
Vol 35 ◽  
pp. 238-239
Author(s):  
J.L. Costa ◽  
D.C. Joy ◽  
D.M. Maher ◽  
K.L. Kirk ◽  
S.W. Hui
Keyword(s):  
Subcellular Localization ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
High Sensitivity ◽  
Spot Size ◽  
Human Platelets ◽  
Parent Molecule ◽  
Low Sensitivity ◽  
Electron Energy Loss

Fluorinated organic molecules have considerable potential as tracers in bio logical systems, since a number of fluorinated analogs demonstrate biological activity similar to that of the parent molecule1. To date, however, the subcellular localization of fluorine has been hampered by the relatively low sensitivity of conventional X-ray microanalysis systems to fluorine. Electron energy-loss spectroscopy, in contrast, is a very efficient method for detecting light elements. We have capitalized on the high sensitivity of this technique to fluorine to identify and localize fluorinated serotonin at a subcellular level in human platelets.Intact human platelets were incubated with 10-5 M concentrations of either serotonin (5HT) or 4,6 difluoroserotonin (DF5HT)2 for 30 minutes at 37°C. Following the incubation period, air-dried whole mounts3 were prepared on 200 mesh copper grids coated with collodion and carbon. Individual platelets were examined at 80 kv in the STEM mode (10 nm spot size), utilizing a Jeol 100B microscope equipped with a field emission gun, a scanning attachment, an electron spectrometer, and a Kevex analysis recording system.

Data Acquisition and Handling Unit for a Quantitative Use of Electron Energy Loss Spectroscopy

1977 ◽  
Vol 35 ◽  
pp. 232-233 ◽  
Author(s):  
P. Trebbia ◽  
P. Ballongue ◽  
C. Colliex
Keyword(s):  
Electron Microscope ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Single Channel ◽  
Detection System ◽  
Surface Barrier ◽  
Solid State Detector ◽  
Electrostatic Mirror ◽  
Electron Energy Loss

An effective use of electron energy loss spectroscopy for chemical characterization of selected areas in the electron microscope can only be achieved with the development of quantitative measurements capabilities.The experimental assembly, which is sketched in Fig.l, has therefore been carried out. It comprises four main elements.The analytical transmission electron microscope is a conventional microscope fitted with a Castaing and Henry dispersive unit (magnetic prism and electrostatic mirror). Recent modifications include the improvement of the vacuum in the specimen chamber (below 10-6 torr) and the adaptation of a new electrostatic mirror.The detection system, similar to the one described by Hermann et al (1), is located in a separate chamber below the fluorescent screen which visualizes the energy loss spectrum. Variable apertures select the electrons, which have lost an energy AE within an energy window smaller than 1 eV, in front of a surface barrier solid state detector RTC BPY 52 100 S.Q. The saw tooth signal delivered by a charge sensitive preamplifier (decay time of 5.10-5 S) is amplified, shaped into a gaussian profile through an active filter and counted by a single channel analyser.

Trends in Electron Energy Loss Spectroscopy

1977 ◽  
Vol 35 ◽  
pp. 228-229
Author(s):  
C. Colliex ◽  
P. Trebbia
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Materials Science ◽  
Analytical Technique ◽  
Recent Developments ◽  
Quantitative Results ◽  
Electron Microscopes ◽  
Electron Energy Loss ◽  
Primary Electrons

The physical foundations for the use of electron energy loss spectroscopy towards analytical purposes, seem now rather well established and have been extensively discussed through recent publications. In this brief review we intend only to mention most recent developments in this field, which became available to our knowledge. We derive also some lines of discussion to define more clearly the limits of this analytical technique in materials science problems.The spectral information carried in both low ( 0<ΔE<100eV ) and high ( >100eV ) energy regions of the loss spectrum, is capable to provide quantitative results. Spectrometers have therefore been designed to work with all kinds of electron microscopes and to cover large energy ranges for the detection of inelastically scattered electrons (for instance the L-edge of molybdenum at 2500eV has been measured by van Zuylen with primary electrons of 80 kV). It is rather easy to fix a post-specimen magnetic optics on a STEM, but Crewe has recently underlined that great care should be devoted to optimize the collecting power and the energy resolution of the whole system.

Signal/Noise Ratio and Elemental Detectivity by Eels

1982 ◽  
Vol 40 ◽  
pp. 488-489
Author(s):  
R. F. Egerton
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Elemental Analysis ◽  
Electron Energy Loss Spectroscopy ◽  
Emission Spectroscopy ◽  
X Ray ◽  
Signal Noise ◽  
Characteristic Signal ◽  
Noise Ratio ◽  
Electron Energy Loss

An important parameter governing the sensitivity and accuracy of elemental analysis by electron energy-loss spectroscopy (EELS) or by X-ray emission spectroscopy is the signal/noise ratio of the characteristic signal.

Quantitative Electron Energy Loss Mapping

1985 ◽  
Vol 43 ◽  
pp. 404-405
Author(s):  
R.D. Leapman ◽  
C.R. Swyt
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Elemental Concentration ◽  
Core Loss ◽  
Elemental Distribution ◽  
Electron Energy Loss

The intensity of a characteristic electron energy loss spectroscopy (EELS) image does not, in general, directly reflect the elemental concentration. In fact, the raw core loss image can give a misleading impression of the elemental distribution. This is because the measured core edge signal depends on the amount of plural scattering which can vary significantly from region to region in a sample. Here, we show how the method for quantifying spectra due to Egerton et al. can be extended to maps.

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