Swift heavy ion induced surface and microstructural evolution in metallic glass thin films

Swift heavy ion induced changes in microstructure and surface morphology of vapor deposited Fe–Ni based metallic glass thin films have been investigated by using atomic force microscopy, X-ray diffraction and transmission electron microscopy. Ion beam irradiation was carried out at room temperature with 103 MeV Au9+ beam with fluences ranging from 3 1011 to 3 1013 ions/cm2. The atomic force microscopy images were subjected to power spectral density analysis and roughness analysis using an image analysis software. Clusters were found in the image of as-deposited samples, which indicates that the film growth is dominated by the island growth mode. As-deposited films were amorphous as evidenced from X-ray diffraction; however, high resolution transmission electron microscopy measurements revealed a short range atomic order in the samples with crystallites of size around 3 nm embedded in an amorphous matrix. X-ray diffraction pattern of the as-deposited films after irradiation does not show any appreciable changes, indicating that the passage of swift heavy ions stabilizes the short range atomic ordering, or even creates further amorphization. The crystallinity of the as-deposited Fe–Ni based films was improved by thermal annealing, and diffraction results indicated that ion beam irradiation on annealed samples results in grain fragmentation. On bombarding annealed films, the surface roughness of the films decreased initially, then, at higher fluences it increased. The observed change in surface morphology of the irradiated films is attributed to the interplay between ion induced sputtering, volume diffusion and surface diffusion

Optimization of parameters of chemical spray pyrolysis technique to get n and p-type layers of SnS

SnS thin films were prepared using automated chemical spray pyrolysis (CSP) technique. Single-phase, p-type, stoichiometric, SnS films with direct band gap of 1.33 eV and having very high absorption coefficient (N105/cm) were deposited at substrate temperature of 375 °C. The role of substrate temperature in determining the optoelectronic and structural properties of SnS films was established and concentration ratios of anionic and cationic precursor solutions were optimized. n-type SnS samples were also prepared using CSP technique at the same substrate temperature of 375 °C, which facilitates sequential deposition of SnS homojunction. A comprehensive analysis of both types of films was done using x-ray diffraction, energy dispersive x-ray analysis, scanning electron microscopy, atomic force microscopy, optical absorption and electrical measurements. Deposition temperatures required for growth of other binary sulfide phases of tin such as SnS2, Sn2S3 were also determined

CuInS2/In2S3 Cells using a Cost-effective Technique: Significance of Precursor Ratios on Cell Parameters

Thin film solar cells having structure CuInS2/In2S3 were fabricated using chemical spray pyrolysis (CSP) technique over ITO coated glass. Top electrode was silver film (area 0.05 cm2). Cu/In ratio and S/Cu in the precursor solution for CuInS2 were fixed as 1.2 and 5 respectively. In/S ratio in the precursor solution for In2S3 was fixed as 1.2/8. An efficiency of 0.6% (fill factor -37.6%) was obtained. Cu diffusion to the In2S3 layer, which deteriorates junction properties, is inevitable in CuInS2/In2S3 cell. So to decrease this effect and to ensure a Cu-free In2S3 layer at the top of the cell, Cu/In ratio was reduced to 1. Then a remarkable increase in short circuit current density was occurred from 3 mA/cm2 to 14.8 mA/cm2 and an efficiency of 2.13% was achieved. Also when In/S ratio was altered to 1.2/12, the short circuit current density increased to 17.8 mA/cm2 with an improved fill factor of 32% and efficiency remaining as 2%. Thus Cu/In and In/S ratios in the precursor solutions play a crucial role in determining the cell parameters

Influence of Major Operational Parameters on Aerobic Granulation for the Treatment of Wastewater

Effective solids-liquid separation is the basic concept of any wastewater treatment system. Biological treatment methods involve microorganisms for the treatment of wastewater. Conventional activated sludge process (ASP) poses the problem of poor settleability and hence require a large footprint. Biogranulation is an effective biotechnological process which can overcome the drawbacks of conventional ASP to a great extent. Aerobic granulation represents an innovative cell immobilization strategy in biological wastewater treatment. Aerobic granules are selfimmobilized microbial aggregates that are cultivated in sequencing batch reactors (SBRs). Aerobic granules have several advantages over conventional activated sludge flocs such as a dense and compact microbial structure, good settleability and high biomass retention. For cells in a culture to aggregate, a number of conditions have to be satisfied. Hence aerobic granulation is affected by many operating parameters. The organic loading rate (OLR) helps to enrich different bacterial species and to influence the size and settling ability of granules. Hence, OLR was argued as an influencing parameter by helping to enrich different bacterial species and to influence the size and settling ability of granules. Hydrodynamic shear force, caused by aeration and measured as superficial upflow air velocity (SUAV), has a strong influence and hence it is used to control the granulation process. Settling time (ST) and volume exchange ratio (VER) are also two key influencing factors, which can be considered as selection pressures responsible for aerobic granulation based on the concept of minimal settling velocity. Hence, these four parameters - OLR, SUAV, ST and VER- were selected as major influencing parametersfor the present study. Influence of these four parameters on aerobic granulation was investigated in this work

Tailoring Magnetic Properties of Co-Fe Thin Films by Topographical Modifications Using Thermal Annealing and Swift Heavy Ion Irradiation and Fabrication of Magnetoelectric Multilayers for Device Applications

Magnetism and magnetic materials have been playing a lead role in improving the quality of life. They are increasingly being used in a wide variety of applications ranging from compasses to modern technological devices. Metallic glasses occupy an important position among magnetic materials. They assume importance both from a scientific and an application point of view since they represent an amorphous form of condensed matter with significant deviation from thermodynamic equilibrium. Metallic glasses having good soft magnetic properties are widely used in tape recorder heads, cores of high-power transformers and metallic shields. Superconducting metallic glasses are being used to produce high magnetic fields and magnetic levitation effect. Upon heat treatment, they undergo structural relaxation leading to subtle rearrangements of constituent atoms. This leads to densification of amorphous phase and subsequent nanocrystallisation. The short-range structural relaxation phenomenon gives rise to significant variations in physical, mechanical and magnetic properties. Magnetic amorphous alloys of Co-Fe exhibit excellent soft magnetic properties which make them promising candidates for applications as transformer cores, sensors, and actuators. With the advent of microminiaturization and nanotechnology, thin film forms of these alloys are sought after for soft under layers for perpendicular recording media. The thin film forms of these alloys can also be used for fabrication of magnetic micro electro mechanical systems (magnetic MEMS). In bulk, they are drawn in the form of ribbons, often by melt spinning. The main constituents of these alloys are Co, Fe, Ni, Si, Mo and B. Mo acts as the grain growth inhibitor and Si and B facilitate the amorphous nature in the alloy structure. The ferromagnetic phases such as Co-Fe and Fe-Ni in the alloy composition determine the soft magnetic properties. The grain correlation length, a measure of the grain size, often determines the soft magnetic properties of these alloys. Amorphous alloys could be restructured in to their nanocrystalline counterparts by different techniques. The structure of nanocrystalline material consists of nanosized ferromagnetic crystallites embedded in an amorphous matrix. When the amorphous phase is ferromagnetic, they facilitate exchange coupling between nanocrystallites. This exchange coupling results in the vanishing of magnetocrystalline anisotropy which improves the soft magnetic properties. From a fundamental perspective, exchange correlation length and grain size are the deciding factors that determine the magnetic properties of these nanocrystalline materials. In thin films, surfaces and interfaces predominantly decides the bulk property and hence tailoring the surface roughness and morphology of the film could result in modified magnetic properties. Surface modifications can be achieved by thermal annealing at various temperatures. Ion irradiation is an alternative tool to modify the surface/structural properties. The surface evolution of a thin film under swift heavy ion (SHI) irradiation is an outcome of different competing mechanism. It could be sputtering induced by SHI followed by surface roughening process and the material transport induced smoothening process. The impingement of ions with different fluence on the alloy is bound to produce systematic microstructural changes and this could effectively be used for tailoring magnetic parameters namely coercivity, saturation magnetization, magnetic permeability and remanence of these materials. Swift heavy ion irradiation is a novel and an ingenious tool for surface modification which eventually will lead to changes in the bulk as well as surface magnetic property. SHI has been widely used as a method for the creation of latent tracks in thin films. The bombardment of SHI modifies the surfaces or interfaces or creates defects, which induces strain in the film. These changes will have profound influence on the magnetic anisotropy and the magnetisation of the specimen. Thus inducing structural and morphological changes by thermal annealing and swift heavy ion irradiation, which in turn induce changes in the magnetic properties of these alloys, is one of the motivation of this study. Multiferroic and magneto-electrics is a class of functional materials with wide application potential and are of great interest to material scientists and engineers. Magnetoelectric materials combine both magnetic as well as ferroelectric properties in a single specimen. The dielectric properties of such materials can be controlled by the application of an external magnetic field and the magnetic properties by an electric field. Composites with magnetic and piezo/ferroelectric individual phases are found to have strong magnetoelectric (ME) response at room temperature and hence are preferred to single phasic multiferroic materials. Currently research in this class of materials is towards optimization of the ME coupling by tailoring the piezoelectric and magnetostrictive properties of the two individual components of ME composites. The magnetoelectric coupling constant (MECC) (_ ME) is the parameter that decides the extent of interdependence of magnetic and electric response of the composite structure. Extensive investigates have been carried out in bulk composites possessing on giant ME coupling. These materials are fabricated by either gluing the individual components to each other or mixing the magnetic material to a piezoelectric matrix. The most extensively investigated material combinations are Lead Zirconate Titanate (PZT) or Lead Magnesium Niobate-Lead Titanate (PMNPT) as the piezoelectric, and Terfenol-D as the magnetostrictive phase and the coupling is measured in different configurations like transverse, longitudinal and inplane longitudinal. Fabrication of a lead free multiferroic composite with a strong ME response is the need of the hour from a device application point of view. The multilayer structure is expected to be far superior to bulk composites in terms of ME coupling since the piezoelectric (PE) layer can easily be poled electrically to enhance the piezoelectricity and hence the ME effect. The giant magnetostriction reported in the Co-Fe thin films makes it an ideal candidate for the ferromagnetic component and BaTiO3 which is a well known ferroelectric material with improved piezoelectric properties as the ferroelectric component. The multilayer structure of BaTiO3- CoFe- BaTiO3 is an ideal system to understand the underlying fundamental physics behind the ME coupling mechanism. Giant magnetoelectric coupling coefficient is anticipated for these multilayer structures of BaTiO3-CoFe-BaTiO3. This makes it an ideal candidate for cantilever applications in magnetic MEMS/NEMS devices. SrTiO3 is an incipient ferroelectric material which is paraelectric up to 0K in its pure unstressed form. Recently few studies showed that ferroelectricity can be induced by application of stress or by chemical / isotopic substitution. The search for room temperature magnetoelectric coupling in SrTiO3-CoFe-SrTiO3 multilayer structures is of fundamental interest. Yet another motivation of the present work is to fabricate multilayer structures consisting of CoFe/ BaTiO3 and CoFe/ SrTiO3 for possible giant ME coupling coefficient (MECC) values. These are lead free and hence promising candidates for MEMS applications. The elucidation of mechanism for the giant MECC also will be the part of the objective of this investigation.

Bayes quadratic unbiased estimator of spatial covariance parameters

This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes estimator of variance components with too many unknown parameters is complicated to be solved analytically. Hence, in order to facilitate the handling with this system, BAIQUE of spatial covariance model with two parameters is considered. Bayesian estimation arises as a solution of a linear equations system which requires the linearity of the covariance functions in the parameters. Here the availability of prior information on the parameters is assumed. This information includes apriori distribution functions which enable to find the first and the second moments matrix. The Bayesian estimation suggested here depends only on the second moment of the prior distribution. The estimation appears as a quadratic form y'Ay , where y is the vector of filtered data observations. This quadratic estimator is used to estimate the linear function of unknown variance components. The matrix A of BAIQUE plays an important role. If such a symmetrical matrix exists, then Bayes risk becomes minimal and the unbiasedness conditions are fulfilled. Therefore, the symmetry of this matrix is elaborated in this work. Through dealing with the infinite series of matrices, a representation of the matrix A is obtained which shows the symmetry of A. In this context, the largest singular value of the decomposed matrix of the infinite series is considered to deal with the convergence condition and also it is connected with Gerschgorin Discs and Poincare theorem. Then the BAIQUE model for some experimental designs is computed and compared. The comparison deals with different aspects, such as the influence of the position of the design points in a fixed interval. The designs that are considered are those with their points distributed in the interval [0, 1]. These experimental structures are compared with respect to the Bayes risk and norms of the matrices corresponding to distances, covariance structures and matrices which have to satisfy the convergence condition. Also different types of the regression functions and distance measurements are handled. The influence of scaling on the design points is studied, moreover, the influence of the covariance structure on the best design is investigated and different covariance structures are considered. Finally, BAIQUE is applied for real data. The corresponding outcomes are compared with the results of other methods for the same data. Thereby, the special BAIQUE, which estimates the general variance of the data, achieves a very close result to the classical empirical variance.

Determination of yield and quality parameters of energy crops applying laboratory and field spectroscopy

A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.

Effects of plant diversity on bioenergy parameters in grassland biomass

Extensive grassland biomass for bioenergy production has long been subject of scientific research. The possibility of combining nature conservation goals with a profitable management while reducing competition with food production has created a strong interest in this topic. However, the botanical composition will play a key role for solid fuel quality of grassland biomass and will have effects on the combustion process by potentially causing corrosion, emission and slagging. On the other hand, botanical composition will affect anaerobic digestibility and thereby the biogas potential. In this thesis aboveground biomass from the Jena-Experiment plots was harvested in 2008 and 2009 and analysed for the most relevant chemical constituents effecting fuel quality and anaerobic digestibility. Regarding combustion, the following parameters were of main focus: higher heating value (HHV), gross energy yield (GE), ash content, ash softening temperature (AST), K, Ca, Mg, N, Cl and S content. For biogas production the following parameters were investigated: substrate specific methane yield (CH4 sub), area specific methane yield (CH4 area), crude fibre (CF), crude protein (CP), crude lipid (CL) and nitrogen-free extract (NfE). Furthermore, an improvement of the fuel quality was investigated through applying the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Through the specific setup of the Jena-Experiment it was possible to outline the changes of these parameters along two diversity gradients: (i) species richness (SR; 1 to 60 species) and (ii) functional group (grasses, legumes, small herbs and tall herbs) presence. This was a novel approach on investigating the bioenergy characteristic of extensive grassland biomass and gave detailed insight in the sward-composition¬ - bioenergy relations such as: (i) the most relevant SR effect was the increase of energy yield for both combustion (annual GE increased by 26% from SR8→16 and by 65% from SR8→60) and anaerobic digestion (annual CH4 area increased by 22% from SR8→16 and by 49% from SR8→60) through a strong interaction of SR with biomass yield; (ii) legumes play a key role for the utilization of grassland biomass for energy production as they increase the energy content of the substrate (HHV and CH4 sub) and the energy yield (GE and CH4 area); (iii) combustion is the conversion technique that will yield the highest energy output but requires an improvement of the solid fuel quality in order to reduce the risk of corrosion, emission and slagging related problems. This was achieved through applying the IFBB-procedure, with reductions in ash (by 23%), N (28%), K (85%), Cl (56%) and S (59%) and equal levels of concentrations along the SR gradient.

Interrelatedness of grazing livestock with vegetation parameters and farmers’ livelihoods in the Mahafaly region, southwestern Madagascar

The study aims to get deeper insight into the highly extensive system of animal husbandry in the Mahafaly region of southwestern Madagascar. It tries to understand the major drivers for pastoral dynamics, land and resource use along a gradient in altitude and vegetation to consider the area’s high spatial and temporal heterogeneity. The study also analyzes the reproductive performance of local livestock as well as the owners’ culling strategies to determine herd dynamics, opportunities for economic growth, and future potential for rural development. Across seasons, plateau herds from both livestock species covered longer distances (cattle 13.6±3.02 km, goats 12.3±3.48 km) and were found further away from the settlements (cattle 3.1±0.96 km, goats 2.8±0.98 km) than those from the coastal plain (walking_dist: cattle 9.5±3.25 km, goats 9.2±2.57 km; max_dist: cattle 2.6±1.28 km, goats 1.8±0.61 km). Transhumant cattle were detected more vulnerable through limited access to pasture land and water resources compared to local herds. Seasonal water shortage has been confirmed as a key constraint on the plateau while livestock keeping along the coast is more limited by dry season forage availability. However, recent security issues and land use conflicts with local crop farmers are gaining importance and force livestock owners to adapt their traditional grazing management, resulting in spatio-temporal variation of livestock numbers and in the impending risk of local overgrazing and degradation of rangelands. Among the 133 plant species consumed by livestock, 13 were determined of major importance for the animals’ nutrition. The nutritive value and digestibility of the natural forage, as well as its abundance in the coastal zone, substantially decreased over the course of the dry season and emphasized the importance of supplementary forage plants, in particular Euphorbia stenoclada. At the same time, an unsustainable utilization and overexploitation of its wild stocks may raise the pressure on the vegetation and pasture resources within the nearby Tsimanampetsotsa National Park. Age at first parturition was 40.5±0.59 months for cattle and 21.3±0.63 months for goats. Both species showed long parturition intervals (cattle 24.2±0.48 months, goats 12.4±0.30 months), mostly due to the maintenance of poorly performing breeding females within the herds. Reported offspring mortality, however, was low with 2.5% of cattle and 18.8% of goats dying before reaching maturity. The analysis of economic information revealed higher than expected market dynamics, especially for zebus, resulting in annual contribution margins of 33 € per cattle unit and 11 € per goat unit. The application of the PRY Herd Life model to simulate herd development for present management and two alternate scenarios confirmed the economic profitability of the current livestock system and showed potential for further productive and economic development. However, this might be clearly limited by the region’s restricted carrying capacity. Summarizing, this study illustrates the highly extensive and resources-driven character of the livestock system in the Mahafaly region, with herd mobility being a central element to cope with seasonal shortages in forage and water. But additional key drivers and external factors are gaining importance and increasingly affect migration decisions and grazing management. This leads to an increased risk of local overgrazing and overexploitation of natural pasture resources and intensifies the tension between pastoral and conservation interests. At the same time, it hampers the region’s agronomic development, which has not yet been fully exploited. The situation therefore demonstrates the need for practical improvement suggestions and implication measures, such as the systematic forestation of supplemental forage plant species in the coastal zone or a stronger integration of animal husbandry and crop production, to sustain the traditional livestock system without compromising peoples’ livelihoods while at the same time minimizing the pastoral impact on the area’s unique nature and environment.

Learning-Based Approach to Estimation of Morphable Model Parameters

We describe the key role played by partial evaluation in the Supercomputing Toolkit, a parallel computing system for scientific applications that effectively exploits the vast amount of parallelism exposed by partial evaluation. The Supercomputing Toolkit parallel processor and its associated partial evaluation-based compiler have been used extensively by scientists at MIT, and have made possible recent results in astrophysics showing that the motion of the planets in our solar system is chaotically unstable.

Model Order Reduction for Determining Bubble Parameters to Attain a Desired Fluid Surface Shape

In this paper, a new methodology for predicting fluid free surface shape using Model Order Reduction (MOR) is presented. Proper Orthogonal Decomposition combined with a linear interpolation procedure for its coefficient is applied to a problem involving bubble dynamics near to a free surface. A model is developed to accurately and efficiently capture the variation of the free surface shape with different bubble parameters. In addition, a systematic approach is developed within the MOR framework to find the best initial locations and pressures for a set of bubbles beneath the quiescent free surface such that the resultant free surface attained is close to a desired shape. Predictions of the free surface in two-dimensions and three-dimensions are presented.

Inference of distributional parameters from compositional samples containing nondetects

Low concentrations of elements in geochemical analyses have the peculiarity of being compositional data and, for a given level of significance, are likely to be beyond the capabilities of laboratories to distinguish between minute concentrations and complete absence, thus preventing laboratories from reporting extremely low concentrations of the analyte. Instead, what is reported is the detection limit, which is the minimum concentration that conclusively differentiates between presence and absence of the element. A spatially distributed exhaustive sample is employed in this study to generate unbiased sub-samples, which are further censored to observe the effect that different detection limits and sample sizes have on the inference of population distributions starting from geochemical analyses having specimens below detection limit (nondetects). The isometric logratio transformation is used to convert the compositional data in the simplex to samples in real space, thus allowing the practitioner to properly borrow from the large source of statistical techniques valid only in real space. The bootstrap method is used to numerically investigate the reliability of inferring several distributional parameters employing different forms of imputation for the censored data. The case study illustrates that, in general, best results are obtained when imputations are made using the distribution best fitting the readings above detection limit and exposes the problems of other more widely used practices. When the sample is spatially correlated, it is necessary to combine the bootstrap with stochastic simulation

ROC parameters in item and context recognition. 'Par??metros ROC en el reconocimiento de items y contextos'

Resumen tomado de la publicaci??n. Resumen tambi??n en ingl??s

Prediction of glucose excursions under uncertain parameters and food intake in intensive insulin therapy for type 1 diabetes mellitus

Considering the difficulty in the insulin dosage selection and the problem of hyper- and hypoglycaemia episodes in type 1 diabetes, dosage-aid systems appear as tremendously helpful for these patients. A model-based approach to this problem must unavoidably consider uncertainty sources such as the large intra-patient variability and food intake. This work addresses the prediction of glycaemia for a given insulin therapy face to parametric and input uncertainty, by means of modal interval analysis. As result, a band containing all possible glucose excursions suffered by the patient for the given uncertainty is obtained. From it, a safer prediction of possible hyper- and hypoglycaemia episodes can be calculated