(XRD) X-Ray Diffraction: (13:54 - 18.03.2011)
XRD involves monitoring the diffraction of X-rays after they interact with the sample. It is a crystallographic technique used for identifying and quantifying various crystalline phases present in solid materials and powders. In XRD, the crystal structure can be determined as well as the size of grains and nanoparticles. When X-rays are directed at a regular crystalline sample, o proportion of them are diffracted to produce a pattern. From such a pattern the crystal phases can be identified by comparison to those of internationally recognized databases (such as International Center of Diffraction Data - ICDD) that contain reference patterns. In sensing applications, XRD is generally used to correlate the properties of a material to its sensing performance.
XRD is one of the most utilized techniques for determining the structure of inorganic and organic materials. It is also widely used for studying nano-structured thin films and nanoparticles. However, the materials must have ordered structure, and it cannot be used directly to study amorphous materials. Another inherent limitation of XRD is that mixtures of phases that have kow symmetry are difficult to differentatiate between because of the larger number of diffraction peaks. Furthermore, organic materials such as polymers are never completely crystalline, therefore XRD is primarily used to determine their crystallinity.
In crystallography, the solid to be characterized by XRD has a space lattice with an ordered three-dimensional distribution of atoms. These atoms form a series of parallel planes seperated by a distance d, which varies according to the nature of the material. For any crystal, planes have their own specific d-spacing. When a monochromatic X-ray beam with wavelength λ is irradiated onto a crystalline material with spacing d, at an angle Θ, diffraction occurs only when the distance traveled by the rays reflected from successive planes differs by an integer number, n of wavelength to produce constructive interference. Such constructive interference patterns only occur when incident angles fulfill the Bragg condition such that:
n.λ = 2d. sinΘ
By varying the angle Θ, the Bragg Law condition is satisfied for different d- spacings in polycrystalline materials.
(Nanotechnology-enabled sensors, Kourosh Kalantar-zadeh,Benjamin Fry, p.237)
Anisotropy: (18.40 - 19.03.2011)
As a result of plastic deformation, the grains have elongated in one direction and contracted in the other. Consequently, this piece of metal has become anisotropic, and thus its properties in the vertical direction are different from those in the horizontal direction. The degree of anisotropy depends on the temperature at which deformation takes place and on how uniformly the metal is deformed.
Anisotropy influences both mechanical and physical properties of metals. For example, sheet steel for electrical transformers is rolled in such a way that the resulting deformation imparts anisotropic magnetic properties to the sheet. This operation reduces magnetic-hysteresis losses and thus improves the efficiency of transformers.
(Kalpakjian S. Schmid S.R.,Manufacturing Engineering and Technology Sixth Edition in SI Units, p. 50)
Erichsen Test: (18.48 - 19.03.2011)
This method is a so-called simulative test, as it mimics industrial deep drawing. The test is usually run on small sheet-metal blanks, which are shaped into cups; the size is generally much smaller than that used inh industrial deep drawing. The punch head used in this test commonly has hemispherical shape. When it is pressed down into the sheet to create the cup, the bottom portion of the cup will of course also be hemispherical. Thus the bottom of the cup will be formed under balanced biaxial conditions. The deformations taking place then will be out of the plane of the sheet specimen.
(Applied Metal Forming: Including FEM Analysis, Henry S. Valberg, p.438)
Analysis of Variance (ANOVA): (21.43 - 19.03.2011)
Analysis of Variance is one of the most popular tests for numerical data and is useful for number of reasons. ANOVA is a general method of studying sampled-data relationships. ANOVA analysis allows the identification of variability from different potential sources. It sets up the analysis of the two sample means from our statistics. Analyzing variance allows for a testing of significant different between class means. The changes in the averages for the data group will be established using the ratio of two estimates of variance: between the groups and within the groups.
The ANOVA procedure is used instead of simpler t-test because significant differences exist in the size of sub-samples. Furthermore, preliminary analysis of descriptive statistics of each sample indicated significant differences in the standart deviations in some cases, again favoring ANOVA instead of simpler t-test.
(Islamic Commmercial Law and Economic Development, Zeeshan Javed Hafeez, p.14)
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