Relation of the Probability of Recoil Atom Ionization to Experimental Data on Ionization by Photons and Electrons

2021 ◽  
Vol 18 (2) ◽  
pp. 173-176
Author(s):  
L. I. Men’shikov ◽  
P. L. Men’shikov ◽  
M. P. Faifman
1969 ◽  
Vol 47 (8) ◽  
pp. 1327-1333 ◽  
Author(s):  
I. G. de Jong ◽  
S. C. Srinivasan ◽  
D. R. Wiles

Experimental evidence is presented which shows that upon neutron irradiation of the compounds Mn2(CO)10, CpMn(CO)3, and CH3CpMn(CO)3 the recoiling 56Mn atom gathers carbonyl radicals to stabilize itself in the group Mn(CO)5, with about 10% radiochemical yield. Basically, the experiments involved addition of iodine to the irradiated compound and identification of the radioactive IMn(CO)5 by carrier techniques. It is suggested that in Mn2(CO)10 targets, the species produced is the •Mn(CO)5 radical itself. Some experimental data are given to show that this radical is stable for over 1 h in the solid at room temperature, but decomposes rapidly above about 60°. The radical decomposes in 20–30 s in solution. In both other target compounds, the species produced is chemically more stable, although it reacts rapidly with iodine. This species is found to be HMn(CO)5, which occurs to the extent of 10–12% in CpMn(CO)3. CH3Mn(CO)5 was also detected in CH3CpMn(CO)3 targets, and its yield was found to be a function of the concentration of isooctane used as diluent in the targets.Results from other studies are discussed in the light of the present data, and it is concluded that in general, in neutron-irradiated metal carbonyl compounds, the recoil atom is able to accumulate carbonyl radicals to a greater extent than is consistent with the composition of the target compound.


Author(s):  
A. Gómez ◽  
P. Schabes-Retchkiman ◽  
M. José-Yacamán ◽  
T. Ocaña

The splitting effect that is observed in microdiffraction pat-terns of small metallic particles in the size range 50-500 Å can be understood using the dynamical theory of electron diffraction for the case of a crystal containing a finite wedge. For the experimental data we refer to part I of this work in these proceedings.


Author(s):  
K.B. Reuter ◽  
D.B. Williams ◽  
J.I. Goldstein

In the Fe-Ni system, although ordered FeNi and ordered Ni3Fe are experimentally well established, direct evidence for ordered Fe3Ni is unconvincing. Little experimental data for Fe3Ni exists because diffusion is sluggish at temperatures below 400°C and because alloys containing less than 29 wt% Ni undergo a martensitic transformation at room temperature. Fe-Ni phases in iron meteorites were examined in this study because iron meteorites have cooled at slow rates of about 10°C/106 years, allowing phase transformations below 400°C to occur. One low temperature transformation product, called clear taenite 2 (CT2), was of particular interest because it contains less than 30 wtZ Ni and is not martensitic. Because CT2 is only a few microns in size, the structure and Ni content were determined through electron diffraction and x-ray microanalysis. A Philips EM400T operated at 120 kV, equipped with a Tracor Northern 2000 multichannel analyzer, was used.


Author(s):  
C. C. Ahn ◽  
D. H. Pearson ◽  
P. Rez ◽  
B. Fultz

Previous experimental measurements of the total white line intensities from L2,3 energy loss spectra of 3d transition metals reported a linear dependence of the white line intensity on 3d occupancy. These results are inconsistent, however, with behavior inferred from relativistic one electron Dirac-Fock calculations, which show an initial increase followed by a decrease of total white line intensity across the 3d series. This inconsistency with experimental data is especially puzzling in light of work by Thole, et al., which successfully calculates x-ray absorption spectra of the lanthanide M4,5 white lines by employing a less rigorous Hartree-Fock calculation with relativistic corrections based on the work of Cowan. When restricted to transitions allowed by dipole selection rules, the calculated spectra of the lanthanide M4,5 white lines show a decreasing intensity as a function of Z that was consistent with the available experimental data.Here we report the results of Dirac-Fock calculations of the L2,3 white lines of the 3d and 4d elements, and compare the results to the experimental work of Pearson et al. In a previous study, similar calculations helped to account for the non-statistical behavior of L3/L2 ratios of the 3d metals. We assumed that all metals had a single 4s electron. Because these calculations provide absolute transition probabilities, to compare the calculated white line intensities to the experimental data, we normalized the calculated intensities to the intensity of the continuum above the L3 edges. The continuum intensity was obtained by Hartree-Slater calculations, and the normalization factor for the white line intensities was the integrated intensity in an energy window of fixed width and position above the L3 edge of each element.


2018 ◽  
Vol 106 (6) ◽  
pp. 603 ◽  
Author(s):  
Bendaoud Mebarek ◽  
Mourad Keddam

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.


1981 ◽  
Vol 20 (04) ◽  
pp. 207-212 ◽  
Author(s):  
J. Hermans ◽  
B. van Zomeren ◽  
J. W. Raatgever ◽  
P. J. Sterk ◽  
J. D. F. Habbema

By means of a case study the choice between several methods of discriminant analysis is presented. Experimental data of a two-groups problem with one or two variables is analysed. The different methods are compared according to posterior probabilities which can be computed for each subject and which are the basis of discriminant analysis. These posterior probabilities are analysed graphically as well as numerically.


2020 ◽  
Vol 39 (4) ◽  
pp. 5905-5914
Author(s):  
Chen Gong

Most of the research on stressors is in the medical field, and there are few analysis of athletes’ stressors, so it can not provide reference for the analysis of athletes’ stressors. Based on this, this study combines machine learning algorithms to analyze the pressure source of athletes’ stadium. In terms of data collection, it is mainly obtained through questionnaire survey and interview form, and it is used as experimental data after passing the test. In order to improve the performance of the algorithm, this paper combines the known K-Means algorithm with the layering algorithm to form a new improved layered K-Means algorithm. At the same time, this paper analyzes the performance of the improved hierarchical K-Means algorithm through experimental comparison and compares the clustering results. In addition, the analysis system corresponding to the algorithm is constructed based on the actual situation, the algorithm is applied to practice, and the user preference model is constructed. Finally, this article helps athletes find stressors and find ways to reduce stressors through personalized recommendations. The research shows that the algorithm of this study is reliable and has certain practical effects and can provide theoretical reference for subsequent related research.


Acta Naturae ◽  
2015 ◽  
Vol 7 (2) ◽  
pp. 42-47 ◽  
Author(s):  
V. V. Gusel’nikova ◽  
D. E. Korzhevskiy

The NeuN protein is localized in nuclei and perinuclear cytoplasm of most of the neurons in the central nervous system of mammals. Monoclonal antibodies to the NeuN protein have been actively used in the immunohistochemical research of neuronal differentiation to assess the functional state of neurons in norm and pathology for more than 20 years. Recently, NeuN antibodies have begun to be applied in the differential morphological diagnosis of cancer. However, the structure of the protein, which can be revealed by antibodies to NeuN, remained unknown until recently, and the functions of the protein are still not fully clear. In the present mini-review, data on NeuN accumulated so far are summarized and analyzed. Data on the structure and properties of the protein, its isoforms, intracellular localization, and hypothesized functions are reported. The application field of immunocytochemical detection of NeuN in scientific and clinical studies, as well as the difficulties in the interpretation of the obtained experimental data and their possible causes, is described in details.


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