Water-responsive carbon nanotubes for selective detection of toxic gases

Ammonia plays an important role in our daily lives and hence its quantitative and qualitative sensing has become necessary. Bulk structure of carbon nanotubes (CNTs) has been employed to detect the gas concentration of 10 ppm. Hydrophobic CNTs were turned to hydrophilic via the application of a ramp electric field that allowed confinement of a controlled amount of water inside CNT microstructure. These samples were then also used to detect different gases. A comparative study has been performed for sensing three reducing gases, namely, ammonia, sulphur-di-oxide, and hydrogen sulphide to elaborate the selectivity of the sensor. A considerable structural bending in the bulk CNT was observed on evaporation of the confined water, which can be accounted to the zipping of individual nanotubes. However, the rate of the stress induced on these bulk microstructures increased on the exposure of ammonia due to the change in the surface tension of the confined solvent. A prototype of an alarm system has been developed to illustrate sensing concept, wherein the generated stress in the bulk CNT induces a reversible loss in electrical contact that changes the equivalent resistance of the electrical circuit upon exposure to the gas. (C) 2015 AIP Publishing LLC.

Making risk minimization tolerant to label noise

In many applications, the training data, from which one needs to learn a classifier, is corrupted with label noise. Many standard algorithms such as SVM perform poorly in the presence of label noise. In this paper we investigate the robustness of risk minimization to label noise. We prove a sufficient condition on a loss function for the risk minimization under that loss to be tolerant to uniform label noise. We show that the 0-1 loss, sigmoid loss, ramp loss and probit loss satisfy this condition though none of the standard convex loss functions satisfy it. We also prove that, by choosing a sufficiently large value of a parameter in the loss function, the sigmoid loss, ramp loss and probit loss can be made tolerant to nonuniform label noise also if we can assume the classes to be separable under noise-free data distribution. Through extensive empirical studies, we show that risk minimization under the 0-1 loss, the sigmoid loss and the ramp loss has much better robustness to label noise when compared to the SVM algorithm. (C) 2015 Elsevier B.V. All rights reserved.

Geomorphology reveals active decollement geometry in the central Himalayan seismic gap

The similar to 700-km-long ``central seismic gap'' is the most prominent segment of the Himalayan front not to have ruptured in a major earthquake during the last 200-500 yr. This prolonged seismic quiescence has led to the proposition that this region, with a population >10 million, is overdue for a great earthquake. Despite the region's recognized seismic risk, the geometry of faults likely to host large earthquakes remains poorly understood. Here, we place new constraints on the spatial distribution of rock uplift within the western similar to 400 km of the central seismic gap using topographic and river profile analyses together with basinwide erosion rate estimates from cosmogenic Be-10. The data sets show a distinctive physiographic transition at the base of the high Himalaya in the state of Uttarakhand, India, characterized by abrupt strike-normal increases in channel steepness and a tenfold increase in erosion rates. When combined with previously published geophysical imaging and seismicity data sets, we interpret the observed spatial distribution of erosion rates and channel steepness to reflect the landscape response to spatially variable rock uplift due to a structurally coherent ramp-flat system of the Main Himalayan Thrust. Although it remains unresolved whether the kinematics of the Main Himalayan Thrust ramp involve an emergent fault or duplex, the landscape and erosion rate patterns suggest that the decollement beneath the state of Uttarakhand provides a sufficiently large and coherent fault segment capable of hosting a great earthquake.

Ferromagnetism and the effect of free charge carriers on electric polarization in the double perovskite Y2NiMnO6

The double perovskite Y2NiMnO6 displays ferromagnetic transition at T-c approximate to 81 K. The ferromagnetic order at low temperature is confirmed by the saturation value of magnetization (Ms) and also validated by the refined ordered magnetic moment values extracted from neutron powder diffraction data at 10 K. This way, the dominant Mn4+ and Ni2+ cationic ordering is confirmed. The cation-ordered P2(1)/n nuclear structure is revealed by neutron powder diffraction studies at 300 and 10 K. Analysis of the frequency-dependent dielectric constant and equivalent circuit analysis of impedance data take into account the bulk contribution to the total dielectric constant. This reveals an anomaly which coincides with the ferromagnetic transition temperature (T-c). Pyrocurrent measurements register a current flow with onset near T-c and a peak at 57 K that shifts with temperature ramp rate. The extrinsic nature of the observed pyrocurrent is established by employing a special protocol measurement. It is realized that the origin is due to reorientation of electric dipoles created by the free charge carriers and not by spontaneous electric polarization at variance with recently reported magnetism-driven ferroelectricity in this material.