scholarly journals Topology and Stability of Conjugated Hydrocarbons. The Dependence of Total π-Electron Energy on Molecular Topology

ChemInform ◽  
2005 ◽  
Vol 36 (35) ◽  
Author(s):  
Ivan Gutman
Keyword(s):  
Electron Energy ◽  
Molecular Topology ◽  
Conjugated Hydrocarbons

scholarly journals Topology and stability of conjugated hydrocarbons: The dependence of total π-electron energy on molecular topology

2005 ◽  
Vol 70 (3) ◽  
pp. 441-456 ◽  
Author(s):  
Ivan Gutman
Keyword(s):  
Present Article ◽  
Molecular Orbital ◽  
Electron Energy ◽  
Molecular Topology ◽  
Total Electron ◽  
Conjugated Hydrocarbons ◽  
Mathematical Properties ◽  
Total Electron Energy ◽  
Orbital Approximation

In spite of the fact that research on the mathematical properties of the total ?-electron energy E (as computed by means of the H?ckel molecular orbital approximation) started already in the 1940s, many results in this area have been obtained also in the newest times. In 1978 this author published in this journal a review on E. The present article is another review on E, summarizing the progress in the theory of E, achieved since then.

scholarly journals Estimating the total π-electron energy

2013 ◽  
Vol 78 (12) ◽  
pp. 1925-1933 ◽  
Author(s):  
Ivan Gutman ◽  
Kinkar Das
Keyword(s):  
Electron Energy ◽  
Upper Bound ◽  
Upper Bounds ◽  
Lower And Upper Bounds ◽  
Total Electron ◽  
Molecular Graphs ◽  
Conjugated Hydrocarbons ◽  
Short Survey ◽  
Total Electron Energy ◽  
Graph Energy

The paper gives a short survey of the most important lower and upper bounds for total ?-electron energy, i.e., graph energy (E). In addition, a new lower and a new upper bound for E are deduced, valid for general molecular graphs. The strengthened versions of these estimates, valid for alternant conjugated hydrocarbons, are also reported.

scholarly journals Monte Carlo Approach to Total π-Electron Energy of Conjugated Hydrocarbons

1985 ◽  
Vol 40 (10) ◽  
pp. 1059-1061
Author(s):  
I. Gutman ◽  
M. Rašković
Keyword(s):  
Monte Carlo ◽  
Distribution Function ◽  
Molecular Orbital ◽  
Electron Energy ◽  
Energy Levels ◽  
Random Variables ◽  
Orbital Energy ◽  
Monte Carlo Approach ◽  
Type Formula ◽  
Conjugated Hydrocarbons

Approximating the π-electron molecular orbital energy levels by uniformly distributed random variables, a McClelland-type formula for the total π-electron energy is obtained. Conditions are determined under which a given distribution function will result in a formula of McClelland type.

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.

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