Spotting 2D atomic layers on aluminum nitride thin films

Substrates for 2D materials are important for tailoring their fundamental properties and realizing device applications. Aluminum nitride (AIN) films on silicon are promising large-area substrates for such devices in view of their high surface phonon energies and reasonably large dielectric constants. In this paper epitaxial layers of AlN on 2 `' Si wafers have been investigated as a necessary first step to realize devices from exfoliated or transferred atomic layers. Significant thickness dependent contrast enhancements are both predicted and observed for monolayers of graphene and MoS2 on AlN films as compared to the conventional SiO2 films on silicon, with calculated contrast values approaching 100% for graphene on AlN as compared to 8% for SiO2 at normal incidences. Quantitative estimates of experimentally measured contrast using reflectance spectroscopy show very good agreement with calculated values. Transistors of monolayer graphene on AlN films are demonstrated, indicating the feasibility of complete device fabrication on the identified layers.

Quantitative characterization of adhesion and stiffness of corneal lens of Drosophila melanogaster using atomic force microscopy

Atomic force Microscopy (AFM) has become a versatile tool in biology due to its advantage of high-resolution imaging of biological samples close to their native condition. Apart from imaging, AFM can also measure the local mechanical properties of the surfaces. In this study, we explore the possibility of using AFM to quantify the rough eye phenotype of Drosophila melanogaster through mechanical properties. We have measured adhesion force, stiffness and elastic modulus of the corneal lens using AFM. Various parameters affecting these measurements like cantilever stiffness and tip geometry are systematically studied and the measurement procedures are standardized. Results show that the mean adhesion force of the ommatidial surface varies from 36 nN to 16 nN based on the location. The mean stiffness is 483 +/- 5 N/m, and the elastic modulus is 3.4 +/- 0.05 GPa (95% confidence level) at the center of ommatidia. These properties are found to be different in corneal lens of eye expressing human mutant tau gene (mutant). The adhesion force, stiffness and elastic modulus are decreased in the mutant. We conclude that the measurement of surface and mechanical properties of D. melanogaster using AFM can be used for quantitative evaluation of `rough eye' surface. (C) 2015 Elsevier Ltd. All rights reserved.

Prediction of electronically nonadiabatic decomposition mechanisms of isolated gas phase nitrogen-rich energetic salt: Guanidium-triazolate

Electronically nonadiabatic decomposition pathways of guanidium triazolate are explored theoretically. Nonadiabatically coupled potential energy surfaces are explored at the complete active space self-consistent field (CASSCF) level of theory. For better estimation of energies complete active space second order perturbation theories (CASPT2 and CASMP2) are also employed. Density functional theory (DFT) with B3LYP functional and MP2 level of theory are used to explore subsequent ground state decomposition pathways. In comparison with all possible stable decomposition products (such as, N-2, NH3, HNC, HCN, NH2CN and CH3NC), only NH3 (with NH2CN) and N-2 are predicted to be energetically most accessible initial decomposition products. Furthermore, different conical intersections between the S-1 and S-0 surfaces, which are computed at the CASSCF(14,10)/6-31G(d) level of theory, are found to play an essential role in the excited state deactivation process of guanidium triazolate. This is the first report on the electronically nonadiabatic decomposition mechanisms of isolated guanidium triazolate salt. (C) 2015 Elsevier B.V. All rights reserved.

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(sigma(2)) operations per pixel, where sigma is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary sigma (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the so-called Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.