Local structural disorder and its influence on the average global structure and polar properties in Na0.5Bi0.5TiO3

Na0.5Bi0.5TiO3 (NBT) and its derivatives have prompted a great surge in interest owing to their potential as lead-free piezoelectrics. In spite of five decades since its discovery, there is still a lack of clarity on crucial issues such as the origin of significant dielectric relaxation at room temperature, structural factors influencing its depoling, and the status of the recently proposed monoclinic (Cc) structure vis-a-vis the nanosized structural heterogeneities. In this work, these issues are resolved by comparative analysis of local and global structures on poled and unpoled NBT specimens using electron, x-ray, and neutron diffraction in conjunction with first-principles calculation, dielectric, ferroelectric, and piezoelectric measurements. The reported global monoclinic (Cc) distortion is shown not to correspond to the thermodynamic equilibrium state at room temperature. The global monocliniclike appearance rather owes its origin to the presence of local structural and strain heterogeneities. Poling removes the structural inhomogeneities and establishes a long-range rhombohedral distortion. In the process the system gets irreversibly transformed from a nonergodic relaxor to a normal ferroelectric state. The thermal depoling is shown to be associated with the onset of incompatible in-phase tilted octahedral regions in the field-stabilized long range rhombohedral distortion.

Macromolecular Crystallography in India in the Global Context

The most spectacular applications of crystallography are currently concerned with biological macromolecules like proteins and their assemblies. Macromolecular crystallography originated in England in the thirties of the last century, but definitive results began to appear only around 1960. Since then macromolecular crystallography has grown to become central to modern biology. India has a long tradition in crystallography starting with the work of K. Banerjee in the thirties. In addition to their contributions to crystallography, G.N. Ramachandran and his colleagues gave a head start to India in computational biology, molecular modeling and what we now call bioinformatics. However, attempts to initiate macromolecular crystallography in India started only in the seventies. The work took off the ground after the Department of Science and Technology handsomely supported the group at Indian Institute of Science, Bangalore in 1983. The Bangalore group was also recognized as a national nucleus for the development of the area in the country. Since then macromolecular crystallography, practiced in more than 30 institutions in the country, has grown to become an important component of scientific research in India. The articles in this issue provide a flavor of activities in the area in the country. The area is still in an expanding phase and is poised to scale greater heights.

Rheological characterization of semi-solid A356 aluminium alloy

Rheological behavior of semi-solid slurries forms the backbone of semi-solid processing of metallic alloys. In particular, the effects of several process and metallurgical parameters such as shear rate, shear time, temperature, rest time and size, distribution and morphology of the primary phase on the viscosity of the slurry needs in-depth characterization. In the present work, rheological behaviour of the semisolid aluminium alloy (A356) slurry is investigated by using a high temperature Searle type Rheometer using concentric cylinders. Three different types of experiment are carried out: isothermal test, continuous cooling test and steady state test. Continuous decrease in viscosity is observed with increasing shear rate at a fixed temperature (isothermal test). It is also found that the viscosity increases with decreasing temperature for a particular shear rate due to increasing solid fraction (continuous cooling test). Thixotropic nature of the slurry is confirmed from the hysteresis loops obtained during experimentation. Time dependence of slurry viscosity has been evaluated from the steady state tests. After a longer shearing time under isothermal conditions the starting dendritic structure of the said alloy is transformed into globular grains due to abrasion, agglomeration, welding and ripening.

Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India

A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.

Ontology analysis of global gene expression differences of human bone marrow stromal cells cultured on 3D scaffolds or 2D films

Differences in gene expression of human bone marrow stromal cells (hBMSCs) during culture in three-dimensional (3D) nanofiber scaffolds or on two-dimensional (2D) films were investigated via pathway analysis of microarray mRNA expression profiles. Previous work has shown that hBMSC culture in nanofiber scaffolds can induce osteogenic differentiation in the absence of osteogenic supplements (OS). Analysis using ontology databases revealed that nanofibers and OS regulated similar pathways and that both were enriched for TGF-beta and cell-adhesion/ECM-receptor pathways. The most notable difference between the two was that nanofibers had stronger enrichment for cell-adhesion/ECM-receptor pathways. Comparison of nanofibers scaffolds with flat films yielded stronger differences in gene expression than comparison of nanofibers made from different polymers, suggesting that substrate structure had stronger effects on cell function than substrate polymer composition. These results demonstrate that physical (nanofibers) and biochemical (OS) signals regulate similar ontological pathways, suggesting that these cues use similar molecular mechanisms to control hBMSC differentiation. Published by Elsevier Ltd.

Phase Field Simulation of Equiaxed Microstructure Formation during Semi-solid Processing of A380 Al Alloy

A phase field modelling approach is implemented in the present study towards simulation of microstructure evolution during cooling slope semi solid slurry generation process of A380 Aluminium alloy. First, experiments are performed to evaluate the number of seeds required within the simulation domain to simulate near spherical microstructure formation, occurs during cooling slope processing of the melt. Subsequently, microstructure evolution is studied employing a phase field method. Simulations are performed to understand the effect of cooling rate on the slurry microstructure. Encouraging results are obtained from the simulation studies which are validated by experimental observations. The results obtained from mesoscopic phase field simulations are grain size, grain density, degree of sphericity of the evolving primary Al phase and the amount of solid fraction present within the slurry at different time frames. Effect of grain refinement also has been studied with an aim of improving the slurry microstructure further. Insight into the process has been obtained from the numerical findings, which are found to be useful for process control.

Ranking of global climate models for India using multicriterion analysis

Eleven GCMs (BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1) were evaluated for India (covering 73 grid points of 2.5 degrees x 2.5 degrees) for the climate variable `precipitation rate' using 5 performance indicators. Performance indicators used were the correlation coefficient, normalised root mean square error, absolute normalised mean bias error, average absolute relative error and skill score. We used a nested bias correction methodology to remove the systematic biases in GCM simulations. The Entropy method was employed to obtain weights of these 5 indicators. Ranks of the 11 GCMs were obtained through a multicriterion decision-making outranking method, PROMETHEE-2 (Preference Ranking Organisation Method of Enrichment Evaluation). An equal weight scenario (assigning 0.2 weight for each indicator) was also used to rank the GCMs. An effort was also made to rank GCMs for 4 river basins (Godavari, Krishna, Mahanadi and Cauvery) in peninsular India. The upper Malaprabha catchment in Karnataka, India, was chosen to demonstrate the Entropy and PROMETHEE-2 methods. The Spearman rank correlation coefficient was employed to assess the association between the ranking patterns. Our results suggest that the ensemble of GFDL2.0, MIROC3, BCCR-BCCM2.0, UKMO-HADCM3, MPIECHAM4 and UKMO-HADGEM1 is suitable for India. The methodology proposed can be extended to rank GCMs for any selected region.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

Formation of annular austenitic ring between outer ferrite layer and solid globule in a semi-solid processed SS 304L

The microstructure of an austenitic SS 304L rapidly quenched from its semi-solid state shows a unique annular austenitic ring in between the core of each globule and its ferritic outer layer. On the basis of experimental results and microstructural analysis, it is proposed that the ring is formed as a result of preferential austenitic phase nucleation in a small quantity of liquid entrapped between adjacent solid globules during rapid quenching, in spite of the fact that ferrite is the thermodynamically stable phase for the alloy. (C) 2014 Elsevier B.V. All rights reserved.

A perturbed martingale approach to global optimization

A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as `coalescence' and `scrambling'. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization. (C) 2014 Elsevier B.V. All rights reserved.

Study of Microstructure Evolution during Semi-Solid Processing of an In-Situ Al Alloy Composite

In the present work, effect of pouring temperature (650 degrees C, 655 degrees C, and 660 degrees C) on semi-solid microstructure evolution of in-situ magnesium silicide (Mg2Si) reinforced aluminum (Al) alloy composite has been studied. The shear force exerted by the cooling slope during gravity driven flow of the melt facilitates the formation of near spherical primary Mg2Si and primary Al grains. Shear driven melt flow along the cooling slope and grain fragmentation have been identified as the responsible mechanisms for refinement of primary Mg2Si and Al grains with improved sphericity. Results show that, while flowing down the cooling slope, morphology of primary Mg2Si and primary Al transformed gradually from coarse dendritic to mixture of near spherical particles, rosettes, and degenerated dendrites. In terms of minimum grain size and maximum sphericity, 650 degrees C has been identified as the ideal pouring temperature for the cooling slope semi-solid processing of present Al alloy composite. Formation of spheroidal grains with homogeneous distribution of reinforcing phase (Mg2Si) improves the isotropic property of the said composite, which is desirable in most of the engineering applications.

Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data

Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.