Gradient echo single scan inversion recovery: application to proton and fluorine relaxation studies

Single scan longitudinal relaxation measurement experiments enable rapid estimation of the spin-lattice relaxation time (T-1) as the time series of spin relaxation is encoded spatially in the sample at different slices resulting in an order of magnitude saving in time. We consider here a single scan inversion recovery pulse sequence that incorporates a gradient echo sequence. The proposed pulse sequence provides spectra with significantly enhanced signal to noise ratio leading to an accurate estimation of T-1 values. The method is applicable for measuring a range of T-1 values, thus indicating the possibility of routine use of the method for several systems. A comparative study of different single scan methods currently available is presented, and the advantage of the proposed sequence is highlighted. The possibility of the use of the method for the study of cross-correlation effects for the case of fluorine in a single shot is also demonstrated. Copyright (C) 2015 John Wiley & Sons, Ltd.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

Simultaneous enhancement of electrical conductivity and thermopower in Bi2S3 under hydrostatic pressure

The inverse coupled dependence of electrical conductivity and thermopower on carrier concentration presents a big challenge in achieving a high figure of merit. However, the simultaneous enhancement of electrical conductivity and thermopower can be realized in practice by carefully engineering the electronic band structure. Here by taking the example of Bi2S3, we report a simultaneous increase in both electrical conductivity and thermopower under hydrostatic pressure. Application of hydrostatic pressure enables tuning of electronic structure in such a way that the conductivity effective mass decreases and the density of states effective mass increases. This dependence of effective masses leads to simultaneous enhancement in electrical conductivity and thermopower under n-type doping leading to a huge improvement in the power factor. Also lattice thermal conductivity exhibits very weak pressure dependence in the low pressure range. The large power factor together with low lattice thermal conductivity results in a high ZT value of 1.1 under n-type doping, which is nearly two times higher than the previously reported value. Hence, this pressure-tuned behaviour can enable the development of efficient thermoelectric devices in the moderate to high temperature range. We further demonstrate that similar enhancement can be observed by generating chemical pressure by doping Bi2S3 with smaller iso-electronic elements such as Sb at Bi sites, which can be achieved experimentally.

Simultaneous tunability of the electronic and phononic gaps in SnS2 under normal compressive strain

Controlled variation of the electronic properties of. two-dimensional (2D) materials by applying strain has emerged as a promising way to design materials for customized applications. Using density functional theory (DFT) calculations, we show that while the electronic structure and indirect band gap of SnS2 do not change significantly with the number of layers, they can be reversibly tuned by applying biaxial tensile (BT), biaxial compressive (BC), and normal compressive (NC) strains. Mono to multilayered SnS2 exhibit a reversible semiconductor to metal (S-M) transition with applied strain. For bilayer (2L) SnS2, the S-Mtransition occurs at the strain values of 17%,-26%, and -24% under BT, BC, and NC strains, respectively. Due to weaker interlayer coupling, the critical strain value required to achieve the S-Mtransition in SnS2 under NC strain is much higher than for MoS2. From a stability viewpoint, SnS2 becomes unstable at very low strain values on applying BC (-6.5%) and BT strains (4.9%), while it is stable even up to the transition point (-24%) in the case of NC strain. In addition to the reversible tuning of the electronic properties of SnS2, we also show tunability in the phononic band gap of SnS2, which increases with applied NC strain. This gap increases three times faster than for MoS2. This simultaneous tunability of SnS2 at the electronic and phononic levels with strain, makes it a potential candidate in field effect transistors (FETs) and sensors as well as frequency filter applications.