Ebook: Immobolization of radioactive waste in ceramic based hosts : Radioactive waste Immobolization : Radioactive waste Immobolization

Ceramic materials have found numerous applications in science, technology and industry as mentioned earlier. One of the recent applications of titania and zirconia based ceramic precursors is in immobilization and solidification of radioactive isotopes in waste effluents coming out of nuclear establishments and power plants. Due to long term stability and integrity of the ceramic waste forms of high and intermediate level nuclear waste, several countries have now switched over from ‘glass technology’ to ‘ceramic technology’ of radwaste management. These and many more applications make ceramics materials an interesting area of research and engineering sciences. The book is particularly aimed at scientific and technical staff in the nuclear and waste management industries in addition to universities and research organizations active in these areas. It will also appeal to a wider audience with interests in environmental issues and will be of benefit to anyone who requires background information on radioactive issues connected with nuclear energy or defense processes, or hazardous waste sources, properties and treatments using crystallographic methods. Auszug aus dem Text Text Sample: Chapter 2, Crystal Structure RefinementAnd instrumentation 2.1, Powder Diffraction method: A major emphasis of materials science is in understanding the elemental compositions and corresponding atomic structures present in materials of interest. This knowledge confirms a material’s purity and suitability for use, and allows explanation for ist properties and performance. Just as chemical elements form a plethora of compounds, so a compound may pack in different arrays to form a variety of distinct crystal structures (known as polymorphs or phases). Elemental composition and physical characteristics such as color and hardness might differentiate phases when encountered in pure form. When in mixtures or reacted with other materials, identification of phases based on physical characteristics or elemental composition can quickly become impossible. Powder diffraction has been the staple analytical tool for chemists and materials scientists for more than 50 years. Powder diffraction is a tool to identify and characterize materials by analyzing the radiation scattering produced when the materials are illuminated with X-rays or neutrons. The patterns formed by the scattered radiation provide an abundance of information from simple fingerprinting to complex structural analysis. X-ray powder diffraction is a powerful non-destructive testing method for determining a range of physical and chemical characteristics of materials. It is widely used in all fields of science and technology [1]. The applications include phase analysis, i.e. the type and quantities of phases present in the sample, the crystallographic unit cell and crystal structure, crystallographic texture, crystalline size, macro-stress and micro strain and also electron radial distribution functions. The usefulness of powder diffraction ranges throughout all areas where materials occur in the crystalline solid state. Uses for powder diffraction are found within the following fields and beyond: Natural Sciences; Materials Science; Pharmaceuticals; Geology and Petrochemicals; Engineering; Metallurgy; Forensics; Conservation and Archaeology. The term ‘powder”, as used in powder diffraction, does not strictly correspond to the usual sense in the word in common language. In powder diffraction the specimen can be a ‘solid substance divided into very small particles” But it can also be a solid block for example of metal, ceramic, polymer, glass or even a thin film or a liquid. The reason for this is that the important parameters for defining the concept of a powder for a diffraction experiment are the number and size of the individual crystallites that form the specimen, and not their degree of accretion [2]. An ‘ideal” powder for a diffraction experiment consists of a large number of small, randomly oriented crystallites (coherently diffracting crystalline domains). If the number is sufficiently large, there are always enough crystallites in any diffracting orientation to give reproducible diffraction patterns. 2.2, Determination of crystal structure: Atomic structure is the most important piece of information about crystalline solids: just from the knowledge of topology of the structure, a precise structural model and many physical properties of crystals can be calculated with state of-the-art quantum-mechanical methods. ‘The ability to determine crystal structures directly from powder diffraction data promises to open up many new avenues of structural science. Many important materials cannot be prepared as single crystals of appropriate size and quality for conventional single crystal diffraction studies, nor indeed for the emerging synchrotron-based microcrystal diffraction techniques. In such cases, structure determination from powder diffraction data may represent the only viable approach for obtaining an understanding of the structural properties of the material of interest [3]”. However, it is important to recognize that structure determination from powder diffraction data is far from routine and significant challenges must be overcome in developing and applying methods for this purpose. For this reason, several research groups have devoted considerable effort in recent years to the development of new and improved techniques in this field. More detailed reviews covering all aspects of structure determination from powder diffraction data may be found in references [4-9]. Crystal structure determination from diffraction data (either single crystal or powder) can be divided into the following stages: (i) unit cell determination and space group assignment, (ii) structure solution, and (iii) structure refinement. The aim of structure solution is to derive an initial approximation to the structure from direct consideration of the experimental diffraction data, but starting from no knowledge of the actual arrangement of atoms or molecules within the unit cell. If the structure solution is a sufficiently good approximation to the true structure, a good quality structure may then be obtained by structure refinement. For powder diffraction data, structure refinement is now carried out fairly routinely using the Rietveld profile refinement technique [10-11], and unit cell determination is carried out using standard indexing procedures (see, for example, references [12-17]. The techniques currently available for structure solution from powder diffraction data can be subdivided into two categories-’traditional’ and ‘direct-space’ approaches. As discussed below, 2.2.1, Conventional approaches: In the traditional approach, the intensities I(hkl) of individual reflections are extracted directly from the powder diffraction pattern, and the structure is then solved using these I(hkl) data in the types of structure solution calculation that are used for single crystal diffraction data (e.g. direct methods or Patterson methods). However, as there is usually extensive peak overlap in the powder diffraction pattern, extracting reliable values of the intensities I(hkl) of the individual diffraction maxima can be problematic, and may lead to difficulties in subsequent attempts to solve the structure using these ‘single-crystal-like’ approaches. To overcome this problem either requires improved techniques for extracting and utilizing peak intensities, or requires the use of new structure solution strategies that allow the experimental powder diffraction profile to be used directly in ist ‘raw’ digitized form, without the requirement to extract the intensities and (hkl) of individual diffraction maxima. 2.2.2, Straight space approaches: In the direct-space approach, trial structures are generated in direct space, independently of the experimental powder diffraction data, with the suitability of each trial structure assessed by direct comparison between the powder diffraction pattern calculated for the trial structure and the experimental powder diffraction pattern. This comparison is quantified using an appropriate R factor. Most direct-space approaches reported to date have used the weighted powder profile R factor Rwp (the R-factor normally employed in Rietveld refinement), although we note that some implementations of direct-space approaches have instead used R-factors based on extracted peak intensities. The basis of the direct-space strategy for structure solution is to find the trial crystal structure corresponding to lowest R-factor, and is equivalent to exploring a hypersurface R (Γ) to find the global minimum, where Γ (capital gama) represents the set of variables that define the structure. In principle, any technique for global optimization may be used to find the lowest point on the R (Γ) hyper surface, and much success has been achieved in using Monte Carlo [18-23], Simulated Annealing [24-30] and Genetic Algorithm [31-36] methods in this field. In addition, grid search methods have also been employed [37-40]. This article focuses on fundamental and applied aspects of our implementations of Monte Carlo (MC) and Genetic Algorithm (GA) techniques within direct space structure solution from powder diffraction data, with particular emphasis on the application of these techniques to elucidate structural properties of molecular materials. Biographische Informationen Dr. Ashish Bohre obtains his Ph.D. degree from Dr. Harisingh Gour Central University Sagar, in 2012. Presently he is working as a post-doctoral research fellow in Delhi University. Dr. Bohre is an author of several research articles and books of international repute.