Brillouin Scattering Studies of La_{0.77}Ca_{0.23}MnO_3 Across Metal-Insulator Transition

Temperature-dependent Brillouin scattering studies have been carried out on La_{0.77}Ca_{0.23}MnO_3 across the paramagnetic insulator - ferromagnetic metal (I-M) transition. The spectra show a surface Rayleigh wave (SRW) and a high velocity pseudo surface acoustic wave (HVPSAW) besides bulk acoustic waves (BAW). The Brillouin shifts associated with SRW and HVPSAW show blue-shifts, where as the frequencies of the BAW decrease below the I-M transition temperature (T_C) of 230 K. These results can be understood based on the temperature dependence of the elastic constants. We also observe a central peak whose width is maximum at T_C.Comment: 7 pages, 8 figure

Crystal structure and physical properties of half-doped manganite nanocrystals with size < 100nm

In this paper we report the structural and property (magnetic and electrical transport) measurements of nanocrystals of half-doped $\mathrm{La_{0.5}Ca_{0.5}MnO_3}$(LCMO) synthesized by chemical route, having particle size down to an average diameter of 15nm. It was observed that the size reduction leads to change in crystal structure and the room temperature structure is arrested so that the structure does not evolve on cooling unlike bulk samples. The structural change mainly affects the orthorhombic distortion of the lattice. By making comparison with observed crystal structure data under hydrostatic pressure it is suggested that the change in the crystal structure of the nanocrystals occurs due to an effective hydrostatic pressure created by the surface pressure on size reduction. This not only changes the structure but also causes the room temperature structure to freeze-in. The size reduction also does not allow the long supercell modulation needed for the Charge Ordering, characteristic of this half-doped manganite, to set-in. The magnetic and transport measurements also show that the Charge Ordering (CO) does not occur when the size is reduced below a critical size. Instead, the nanocrystals show ferromagnetic ordering down to the lowest temperatures along with metallic type conductivity. Our investigation establishes a structural basis for the destabilization of CO state observed in half-doped manganite nanocrystals.Comment: 11 pages, 13 Figure

Current-induced phase control in charged-ordered Nd0.5Ca0.5MnO3 and Pr0.6Ca0.4MnO3 crystals

Single crystals of Nd0.5Ca0.5MnO3 and Pr0.6Ca0.4MnO3 show current-induced insulator-metal transitions at low temperatures. In addition, the charge-ordering transition temperature decreases with increasing current. The electroresistive ratio, defined as r0.5/rI where r0.5 is the resistivity at a current of 0.5 mA and rI the resistivity at a given applied current, I, varies markedly with temperature and the value of I. Thermal hysteresis observed in Nd0.5Ca0.5MnO3 and Pr0.6Ca0.4MnO3 at the insulator-metal transition indicates that the transition is first-order. The current-induced changes are comparable to those induced by magnetic fields, and the insulator-metal transition in Pr0.6Ca0.4MnO3 is accordingly associated with a larger drop in resistivity.Comment: 12 pages, 3 figures, first submitted to submitted to J. Phys. D; applied physics on 18th march 200

Non-Destructive Evaluation—A Pivotal Technology for Qualification of Composite Aircraft Structures

Tremendous advances in composite materials and a deeper understanding of their behavior have been responsible for the increased use of composites in the development of advanced, new generation civil and military aircraft. Composites play an important role in any aircraft development programme and are strong contenders to their metal counterparts due to their significant contributions towards improving strength, stiffness, fatigue properties & weight reduction. As materials, structural design & processing have evolved, strong emphasis is placed on effective & reliable damage detection, durability and damage tolerance. As a consequence, Non-destructive Evaluation (NDE) has also undergone significant advances towards meeting the growing demands of quality assurance. Advanced Composites Division (ACD) of National Aerospace Laboratories (NAL), has been involved in the development of composite structures for both civil and military aircraft for over a decade and a half. Innovative composite processing methods like co-curing/co-bonding have been successfully employed to realize airworthy structures. The role of NDE in the development of these structures has been critical and not limited to damage detection alone. On several occasions, NDE has provided valuable inputs towards improving design and process parameters. In-spite of the complexity of the structures, stringent quality requirements and tight delivery schedules, NDE has been successful in certifying these composite structures for airworthiness. This paper discusses the implementation of key NDE techniques like ultrasonics, radiography, acoustic emission and thermography for reliable flaw detection, characterization and quality assurance of composite aircraft structures

Beyond Short Snippets: Deep Networks for Video Classification

Convolutional neural networks (CNNs) have been extensively applied for image recognition problems giving state-of-the-art results on recognition, detection, segmentation and retrieval. In this work we propose and evaluate several deep neural network architectures to combine image information across a video over longer time periods than previously attempted. We propose two methods capable of handling full length videos. The first method explores various convolutional temporal feature pooling architectures, examining the various design choices which need to be made when adapting a CNN for this task. The second proposed method explicitly models the video as an ordered sequence of frames. For this purpose we employ a recurrent neural network that uses Long Short-Term Memory (LSTM) cells which are connected to the output of the underlying CNN. Our best networks exhibit significant performance improvements over previously published results on the Sports 1 million dataset (73.1% vs. 60.9%) and the UCF-101 datasets with (88.6% vs. 88.0%) and without additional optical flow information (82.6% vs. 72.8%)