Engineered spin-valve type magnetoresistance in Fe3O4-CoFe2O4 core-shell nanoparticles

Naturally occurring spin-valve-type magnetoresistance (SVMR), recently observed in Sr2FeMoO6 samples, suggests the possibility of decoupling the maximal resistance from the coercivity of the sample. Here we present the evidence that SVMR can be engineered in specifically designed and fabricated core-shell nanoparticle systems, realized here in terms of soft magnetic Fe3O4 as the core and hard magnetic insulator CoFe2O4 as the shell materials. We show that this provides a magnetically switchable tunnel barrier that controls the magnetoresistance of the system, instead of the magnetic properties of the magnetic grain material, Fe3O4, and thus establishing the feasibility of engineered SVMR structures. (C) 2013 AIP Publishing LLC.

Image reconstruction enables high resolution imaging at large penetration depths in fluorescence microscopy

Imaging thick specimen at a large penetration depth is a challenge in biophysics and material science. Refractive index mismatch results in spherical aberration that is responsible for streaking artifacts, while Poissonian nature of photon emission and scattering introduces noise in the acquired three-dimensional image. To overcome these unwanted artifacts, we introduced a two-fold approach: first, point-spread function modeling with correction for spherical aberration and second, employing maximum-likelihood reconstruction technique to eliminate noise. Experimental results on fluorescent nano-beads and fluorescently coated yeast cells (encaged in Agarose gel) shows substantial minimization of artifacts. The noise is substantially suppressed, whereas the side-lobes (generated by streaking effect) drops by 48.6% as compared to raw data at a depth of 150 mu m. Proposed imaging technique can be integrated to sophisticated fluorescence imaging techniques for rendering high resolution beyond 150 mu m mark. (C) 2013 AIP Publishing LLC.

Predictability of nonstationary time series using wavelet and EMD based ARMA models

Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology. (C) 2013 Elesvier B.V. All rights reserved.

Investigation on non-exchange spring behaviour and exchange spring behaviour: A first order reversal curve analysis

The First Order Reversal Curve (FORC) method has been utilised to understand the magnetization reversal and the extent of the irreversible magnetization of the soft CoFe2O4-hard SrFe12O19 nanocomposite in the nonexchange spring and the exchange spring regime. The single peak switching behaviour in the FORC distribution of the exchange spring composite confirms the coherent reversal of the soft and hard phases. The onset of the nucleation field and the magnetization reversal by domain wall movement are also evident from the FORC measurements. (C) 2013 AIP Publishing LLC.

An early in-situ stress signature of the AlN-Si pre-growth interface for successful integration of nitrides with (111) Si

The integration of Metal Organic Chemical Vapor Deposition (MOCVD) grown group III-A nitride device stacks on Si (111) substrates is critically dependent on the quality of the first AlN buffer layer grown. A Si surface that is both oxide-free and smooth is a primary requirement for nucleating such layers. A single parameter, the AlN layer growth stress, is shown to be an early (within 50 nm), clear (<0.5 GPa versus > 1GPa), and fail-safe indicator of the pre-growth surface, and the AlN quality required for successful epitaxy. Grain coalescence model for stress generation is used to correlate growth stress, the AlN-Si interface, and crystal quality. (C) 2013 AIP Publishing LLC.

Excellent Performance of Few-Layer Borocarbonitrides as Anode Materials in Lithium-Ion Batteries

Borocarbonitrides (BxCyNz) with a graphene-like structure exhibit a remarkable high lithium cyclability and current rate capability. The electrochemical performance of the BxCyNz materials, synthesized by using a simple solid-state synthesis route based on urea, was strongly dependent on the composition and surface area. Among the three compositions studied, the carbon-rich compound B0.15C0.73N0.12 with the highest surface area showed an exceptional stability (over 100cycles) and rate capability over widely varying current density values (0.05-1Ag(-1)). B0.15C0.73N0.12 has a very high specific capacity of 710mAhg(-1) at 0.05Ag(-1). With the inclusion of a suitable additive in the electrolyte, the specific capacity improved drastically, recording an impressive value of nearly 900mAhg(-1) at 0.05Ag(-1). It is believed that the solid-electrolyte interphase (SEI) layer at the interface of BxCyNz and electrolyte also plays a crucial role in the performance of the BxCyNz .