Statistical Analysis of Flaw Strength Spectra of High-Modulus Fibers

2009 ◽  
pp. 77-77-13 ◽  
Author(s):  
SL Phoenix
Keyword(s):  
Statistical Analysis ◽  
High Modulus

Statistical analysis of the scale factor in the strength of high-modulus fibres

1993 ◽  
Vol 24 (2) ◽  
pp. 123-126
Author(s):  
M. P. Nosov ◽  
V. A. Smirnova ◽  
V. I. Pirogov
Keyword(s):  
Statistical Analysis ◽  
Scale Factor ◽  
High Modulus

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

EXELFS Studies of Carbon Fibers

1990 ◽  
Vol 48 (2) ◽  
pp. 72-73
Author(s):  
V. Serin ◽  
K. Hssein ◽  
G. Zanchi ◽  
J. Sévely
Keyword(s):  
Carbon Fibers ◽  
Energy Analysis ◽  
Electron Excitation ◽  
Complex Structures ◽  
High Modulus ◽  
Promising Technique ◽  
X Ray ◽  
Fine Structures ◽  
X Ray Absorption

The present developments of electron energy analysis in the microscopes by E.E.L.S. allow an accurate recording of the spectra and of their different complex structures associated with the inner shell electron excitation by the incident electrons (1). Among these structures, the Extended Energy Loss Fine Structures (EXELFS) are of particular interest. They are equivalent to the well known EXAFS oscillations in X-ray absorption spectroscopy. Due to the EELS characteristic, the Fourier analysis of EXELFS oscillations appears as a promising technique for the characterization of composite materials, the major constituents of which are low Z elements. Using EXELFS, we have developed a microstructural study of carbon fibers. This analysis concerns the carbon K edge, which appears in the spectra at 285 eV. The purpose of the paper is to compare the local short range order, determined by this way in the case of Courtauld HTS and P100 ex-polyacrylonitrile carbon fibers, which are high tensile strength (HTS) and high modulus (HM) fibers respectively.

Autonomous self-healing polyisoprene elastomers with high modulus and good toughness based on the synergy of dynamic ionic crosslinks and highly disordered crystals

2020 ◽  
Vol 11 (41) ◽  
pp. 6549-6558
Author(s):  
Yohei Miwa ◽  
Mayu Yamada ◽  
Yu Shinke ◽  
Shoichi Kutsumizu
Keyword(s):  
Mechanical Properties ◽  
Room Temperature ◽  
Self Healing ◽  
High Modulus ◽  
Disordered Crystals ◽  
Ionic Crosslinks

We designed a novel polyisoprene elastomer with high mechanical properties and autonomous self-healing capability at room temperature facilitated by the coexistence of dynamic ionic crosslinks and crystalline components that slowly reassembled.

Sign in / Sign up

Export Citation Format

Share Document