Effect of the A cation size disorder and synthesis conditions on the properties of an iron perovskite series

Póster presentado en The Energy and Materials Research Conference - EMR2015 celebrado en Madrid (España) entre el 25-27 de febrero de 2015

Deformation behaviour of electrodeposited nanocrystalline Ni with broad grain size distribution

In the present work, nanocrystalline Ni (nc-Ni) with a broad grain size distribution (BGSD) of 5-120 nm and an average grain size of 27.2 nm was prepared. The BGSD nc-Ni sample shows a similar strength and good ductility in comparison with electrodeposited nc-Ni with a narrow grain size distribution. The intracrystalline dislocation network was observed in the post-deformed microstructure confirming the conventional intracrystalline dislocation sliding mechanism in BGSD nc-Ni. The uniaxial tensile loading-unloading-loading deformation shows BGSD nc-Ni has the capability to store dislocations in the grain interior, which is very limited compared with that of coarse grained metals. For BGSD nc-Ni, the strain rate sensitivity of flow stress m enhances with decreasing strain rate. At the strain rate of 5 x 10(-6) s(-1), m was estimated to be 0.055. At the corresponding strain rate, the enhanced ductility along with the decreased strength was achievable, indicating activation of other deformation mechanisms, e. g. grain boundary sliding or diffusion.

The effects of sediment transport on grain-size distributions

Changes in statistics (mean, sorting, and skewness) describing grain-size distributions have long been used to speculate on the direction of sediment transport. We present a simple model whereby the distributions of sediment in transport are related to their source by a sediment transfer function which defines the relative probability that a grain within each particular class interval will be eroded and transported. A variety of empirically derived transfer functions exhibit negatively skewed distributions (on a phi scale). Thus, when a sediment is being eroded, the probability of any grain going into transport increases with diminishing grain size throughout more than half of its size range. This causes the sediment in transport to be finer and more negatively skewed than its source, whereas the remaining sediment (a lag) must become relatively coarser and more positively skewed. Flume experiments show that the distributions of transfer functions change from having a highly negative skewness to being nearly symmetrical (although still negatively skewed) as the energy of the transporting process increases. We call the two extremes low-energy and high-energy transfer functions , respectively. In an expanded sediment-transport model, successive deposits in the direction of transport are related by a combination of two transfer functions. If energy is decreasing and the transfer functions have low-energy distributions, successive deposits will become finer and more negatively skewed. If, however, energy is decreasing, but the initial transfer function has a high-energy distribution, successive deposits will become coarser and more positively skewed. The variance of the distributions of lags, sediment in transport, and successive deposits in the down-current direction must eventually decrease (i.e., the sediments will become better sorted). We demonstrate that it is possible for variance first to increase, but suggest that, in reality, an increasing variance in the direction of transport will seldom be observed, particularly when grain-size distributions are described in phi units. This model describing changes in sediment distributions was tested in a variety of environments where the transport direction was known. The results indicate that the model has real-world validity and can provide a method to predict the directions of sediment transport

Brazos River bar; a study in the significance of grain size parameters

A bar on the Brazos River near Calvert, Texas, has been analyzed in order to determine the geologic meaning of certain grain size parameters and to study the behavior of the size fractions with transport. The bar consists of a strongly bimodal mixture of pebble gravel and medium to fine sand; there is a lack of material in the range of 0.5 to 2 mm, because the source does not supply particles of this size. The size distributions of the two modes, which were established in the parent deposits, are nearly invariant over the bar because the present environment of deposition only affects the relative proportions of the two modes, not the grain size properties of the modes themselves. Two proportions are most common; the sediment either contains no gravel or else contains about 60% gravel. Three sediment types with characteristic bedding features occur on the bar in constant stratigraphic order, with the coarsest at the base. Statistical analysis of the data is based on a series of grain size parameters modified from those of Inman (1952) to provide a more detailed coverage of non-normal size curves. Unimodal sediments have nearly normal curves as defined by their skewness and kurtosis. Non-normal kurtosis and skewness values are held to be the identifying characteristics of bimodal sediments even where such modes are not evident in frequency curves. The relative proportions of each mode define a systematic series of changes in numerical properties; mean size, standard deviation and skewness are shown to be linked in a helical trend, which is believed to be applicable to many other sedimentary suites. The equations of the helix may be characteristic of certain environments. Kurtosis values show rhythmic pulsations along the helix and are diagnostic of two-generation sediments.

Preliminary analysis of grain-size populations with environmentally sensitive terrigenous components in marginal sea setting

Terrigenous components were separated from the bulk sediment of Core A7 from the Okinawa Trough and Core A37 from the Ryukru Trench and grain-size distributions of these sub-samples were analyzed. Based upon an analysis of the grain-size data of the two sedimentary sequences, grain-size populations are identified to be sensitive to sedimentary environmental changes. The modal values and size ranges of the two main grain-size populations in Core A7 are evidently different from those of Core A37, indicating the spatial variability of sediment sources and transport processes between the two places. The downcore variations in the content of the environmentally sensitive grain-size populations reveal that during the accumulation of sedimentary material the environment remained relatively stable at the site where Core A7 was collected, except for the apparent events for the formation of two turbidite layers and a volcanic ash layer. However, the sedimentary sequence of Core A37 shows six sedimentary cycles, indicating a highly variable sedimentary environment at this location.

Grain size distribution of quartz isolated from Chinese loess/paleosol

Grain size distribution of bulk loess-paleosol and quartz chemically extracted from the loess/paleosol shows that mean size of the bulk samples is always finer than that of the quartz, The original aeolian depositions have been modified to various degrees by post-depositional weathering and pedogenic processes. The grain size distribution of the isolated quartz should be close to that of the primary aeolian sediment because the chemical pretreatment excludes secondary produced minerals. Therefore, the grain size of the quartz may be considered to more clearly reflect the variations of winter monsoon intensity.

Grain-size records at ODP site 1146 from the northern South China sea: Implications on the east Asian monsoon evolution since 20 Ma

273 samples from Ocean Drilling Program (ODP) Site 1146 in the northern South China Sea (SCS) were analyzed for grain-size distributions using grain-size class vs. standard deviation method and end-member modeling algorithm (EMMA) in order to investigate the evolution of the East Asian mon-soon since about 20 Ma. 10-19 mu m/1.3-2.4 mu m, the ratio of two grain-size populations with the highest variability through time was used to indicate East Asian winter monsoon intensity relative to summer monsoon. The mass accumulation rate of the coarsest end member EM1 (eolian), resulting from EMMA, can be used as a proxy of winter monsoon strength and Asian inland aridity, and the ratio of EM1/(EM2+EM3) as a proxy of winter monsoon intensity relative to summer monsoon. The combined proxies show that a profound enhancement of East Asian winter monsoon strength and winter monsoon intensity relative to summer monsoon occurred at about 8 Ma, and it is possible that the summer monsoon simultaneously intensified with winter monsoon at 3 Ma. Our results are well consistent with the previous studies in loess, eolian deposion in the Pacifc, radiolarians and planktonic foraminifera in the SCS. The phased uplift of the Himalaya-Tibetan Plateau may have played a significant role in strengthening the Asian monsoon at 8 Ma and 3 Ma.

Learning Embeddings for Indexing, Retrieval, and Classification, with Applications to Object and Shape Recognition in Image Databases

Nearest neighbor retrieval is the task of identifying, given a database of objects and a query object, the objects in the database that are the most similar to the query. Retrieving nearest neighbors is a necessary component of many practical applications, in fields as diverse as computer vision, pattern recognition, multimedia databases, bioinformatics, and computer networks. At the same time, finding nearest neighbors accurately and efficiently can be challenging, especially when the database contains a large number of objects, and when the underlying distance measure is computationally expensive. This thesis proposes new methods for improving the efficiency and accuracy of nearest neighbor retrieval and classification in spaces with computationally expensive distance measures. The proposed methods are domain-independent, and can be applied in arbitrary spaces, including non-Euclidean and non-metric spaces. In this thesis particular emphasis is given to computer vision applications related to object and shape recognition, where expensive non-Euclidean distance measures are often needed to achieve high accuracy. The first contribution of this thesis is the BoostMap algorithm for embedding arbitrary spaces into a vector space with a computationally efficient distance measure. Using this approach, an approximate set of nearest neighbors can be retrieved efficiently - often orders of magnitude faster than retrieval using the exact distance measure in the original space. The BoostMap algorithm has two key distinguishing features with respect to existing embedding methods. First, embedding construction explicitly maximizes the amount of nearest neighbor information preserved by the embedding. Second, embedding construction is treated as a machine learning problem, in contrast to existing methods that are based on geometric considerations. The second contribution is a method for constructing query-sensitive distance measures for the purposes of nearest neighbor retrieval and classification. In high-dimensional spaces, query-sensitive distance measures allow for automatic selection of the dimensions that are the most informative for each specific query object. It is shown theoretically and experimentally that query-sensitivity increases the modeling power of embeddings, allowing embeddings to capture a larger amount of the nearest neighbor structure of the original space. The third contribution is a method for speeding up nearest neighbor classification by combining multiple embedding-based nearest neighbor classifiers in a cascade. In a cascade, computationally efficient classifiers are used to quickly classify easy cases, and classifiers that are more computationally expensive and also more accurate are only applied to objects that are harder to classify. An interesting property of the proposed cascade method is that, under certain conditions, classification time actually decreases as the size of the database increases, a behavior that is in stark contrast to the behavior of typical nearest neighbor classification systems. The proposed methods are evaluated experimentally in several different applications: hand shape recognition, off-line character recognition, online character recognition, and efficient retrieval of time series. In all datasets, the proposed methods lead to significant improvements in accuracy and efficiency compared to existing state-of-the-art methods. In some datasets, the general-purpose methods introduced in this thesis even outperform domain-specific methods that have been custom-designed for such datasets.

Exploring grain size as a cause for dead-layer effects in thin film capacitors

Pulsed laser deposition was used to make a series of Au/Ba0.5Sr0.5TiO3 (BST)/SrRuO3/MgO thin film capacitors with dielectric thickness ranging from similar to15 nm to similar to1 mum. Surface grain size of the dielectric was monitored as a function of thickness using both atomic force microscopy and transmission electron microscopy. Grain size data were considered in conjunction with low field dielectric constant measurements. It was observed that the grain size decreased with decreasing thickness in a manner similar to the dielectric constant. Simple models were developed in which a functionally inferior layer at the grain boundary was considered as responsible for the observed dielectric behavior. If a purely columnar microstructure was assumed, then constant thickness grain-boundary dead layers could indeed reproduce the series capacitor dielectric response observed, even though such layers would contribute electrically in parallel with unaffected bulk- like BST. Best fits indicated that the dead layers would have a relative dielectric constant similar to40, and thickness of the order of tens of nanometers. For microstructures that were not purely columnar, models did not reproduce the observed dielectric behavior well. However, cross-sectional transmission electron microscopy indicated columnar microstructure, suggesting that grain boundary dead layers should be considered seriously in the overall dead-layer debate. (C) 2002 American Institute of Physics.

INFLUENCE OF METAL GRAIN-SIZE ON SURFACE-ENHANCED RAMAN-SCATTERING

The surface roughness of nominally smooth and of randomly roughened thin silver films is characterized using scanning tunneling microscopy and the metal grain size is assessed using transmission electron microscopy. On each type of substrate used, glass or CaF2-roughened glass, the silver films are deposited either very slowly (approximately 0.15 nm s-1) or quite quickly (approximately 2.0 nm s-1). Only silver films deposited on CaF2-roughened glass yield measurable surface-enhanced Raman signals for benzoic acid; the enhancement is brought about by surface field amplification due to the excitation of delocalized surface-plasmon polaritons. However, the surface-enhanced Raman signals obtained from the slow-deposited silver films are significantly better (by about a factor of 3) than those obtained from the fast-deposited silver films on a given CaF2-roughened substrate. The explanation of this observation does not lie with different surface roughness; both types of film yield closely similar data on the scanning tunneling microscope. Rather, it is suggested that the relatively small grain size of the fast-deposited silver films leads to increased elastic scattering of surface-plasmon polaritons at the grain boundaries, with a consequent increase of internal damping. This results in a reduction of the scattered Raman signal.

Effective grain size distribution analysis for interpretation of tidal-deltaic facies: West Bengal Sundarbans

Research over the past two decades on the Holocene sediments from the tide dominated west side of the lower Ganges delta has focussed on constraining the sedimentary environment through grain size distributions (GSD). GSD has traditionally been assessed through the use of probability density function (PDF) methods (e.g. log-normal, log skew-Laplace functions), but these approaches do not acknowledge the compositional nature of the data, which may compromise outcomes in lithofacies interpretations. The use of PDF approaches in GSD analysis poses a series of challenges for the development of lithofacies models, such as equifinal distribution coefficients and obscuring the empirical data variability. In this study a methodological framework for characterising GSD is presented through compositional data analysis (CODA) plus a multivariate statistical framework. This provides a statistically robust analysis of the fine tidal estuary sediments from the West Bengal Sundarbans, relative to alternative PDF approaches.

Investigations on The Finite Size Effects of Some Inverse Spinels and Studies on Their Composites Based on Nitrile Rubber

Magnetism and magnetic materials have been an ever-attractive subject area for engineers and scientists alike because of its versatility in finding applications in useful devices. They find applications in a host of devices ranging from rudimentary devices like loud speakers to sophisticated gadgets like waveguides and Magnetic Random Access Memories (MRAM).The one and only material in the realm of magnetism that has been at the centre stage of applications is ferrites and in that spinel ferrites received the lions share as far as practical applications are concerned.It has been the endeavour of scientists and engineers to remove obsolescence and improve upon the existing so as to save energy and integrate in to various other systems. This has been the hallmark of material scientists and this has led to new materials and new technologies.In the field of ferrites too there has been considerable interest to devise new materials based on iron oxides and other compounds. This means synthesising ultra fine particles and tuning its properties to device new materials. There are various preparation techniques ranging from top- down to bottom-up approaches. This includes synthesising at molecular level, self assembling,gas based condensation. Iow temperature eo-precipitation, solgel process and high energy ball milling. Among these methods sol-gel process allows good control of the properties of ceramic materials. The advantage of this method includes processing at low temperature. mixing at the molecular level and fabrication of novel materials for various devices.Composites are materials. which combine the good qualities of one or more components. They can be prepared in situ or by mechanical means by the incorporation of fine particles in appropriate matrixes. The size of the magnetic powders as well as the nature of matrix affect the processability and other physical properties of the final product. These plastic/rubber magnets can in turn be useful for various applications in different devices. In applications involving ferrites at high frequencies, it is essential that the material possesses an appropriate dielectric permittivity and suitable magnetic permeability. This can be achieved by synthesizing rubber ferrite composites (RFC's). RFCs are very useful materials for microwave absorptions. Hence the synthesis of ferrites in the nanoregirne.investigations on their size effects on the structural, magnetic, and electrical properties and the incorporation of these ferrites into polymer matrixes assume significance.In the present study, nano particles of NiFe204, Li(!5Fe2S04 and Col-e-O, are prepared by sol gel method. By appropriate heat treatments, particles of different grain sizes are obtained. The structural, magnetic and electrical measurements are evaluated as a function of grain size and temperature. NiFel04 prepared in the ultrafine regime are then incorporated in nitrile rubber matrix. The incorporation was carried out according to a specific recipe and for various loadings of magnetic fillers. The cure characteristics, magnetic properties, electrical properties and mechanical properties of these elastomer blends are carried out. The electrical permittivity of all the rubber samples in the X - band are also conducted.