Effect of 100 KeV Ar+ ion beam irradiation on ZnO thin films – Influence of morphology vis-a-vis electrode/electrolyte interface and its impact on photoelectrochemical water splitting

The present study attempts quantitative determination of changes in the morphological surface features viz. fractal dimension, lower and upper cut off length scale through Power Spectral Density analysis prior to and after irradiation of 100 KeV Ar⁺ ion beam at incidence angles of 0°, 40° and 60° on ZnO thin films. All the unirradiated and irradiated samples are subjected to photoelectrochemical characterization and a correlation between photoelectrochemical performance and morphological parameters is established. Sample irradiated at 40° angle at the fluence of 5 × 10¹⁶ ions/cm² is found to possess maximum fractal dimension of 2.72, lower and upper cut off length scale of 3.16 nm and 63.00 nm respectively. This sample exhibits maximum photocurrent density of 3.19 mA/cm² and applied bias photon-to-current efficiency of 1.12% at 1.23 V/RHE. Hydrogen gas collected for duration of 1 h for the same sample was ~4.83 mLcm^?2.     

Carbon-based TiO2-x heterostructure nanocomposites for enhanced photocatalytic degradation of dye molecules

Application of brown titanium dioxide (TiO_2-x) and its modified composite forms in the photocatalytic decomposition of organic pollutants in the environment is a promising way to provide solutions for environmental redemption. Herein, we report the synthesis of effective and stable TiO_2-x nanoparticles with g-C₃N₄, RGO, and multiwalled carbon nanotubes (CNTs) using a simple hydrothermal method. Among all the as-synthesized samples, excellent photocatalytic degradation activity was observed for RGO-TiO_2-x nanocomposite with high rate constants of 0.075 min^?1_, 0.083 min^?1 and 0.093 min^?1 for methylene blue, rhodamine-B, and rosebengal dyes under UV–Visible light irradiation, respectively. The altered bandgap (1.8 eV) and the large surface area of RGO-TiO_2-x nanocomposite impacts on both absorption of visible light and efficiency of photogenerated charge electron (e^?)/hole (h⁺) pair separation. This resulted in enhanced photocatalytic property of carbon-based TiO_2-x nanocomposites. A systematic study on the influence of different carbon nanostructures on the photocatalytic activity of brown TiO_2-x is carried out.     

A machine learning system for identifying transmembrane domains from amino acid sequences

We present our machine learning system, that uses inductive logic programming techniques to learn how to identify transmembrane domains from amino acid sequences. Our system facilitates the use of operators such as ‘contains’, that act on entire sequences, rather than on individual elements of a sequence. The prediction accuracy of our new system is around 93%, and this compares favourably with earlier results. This work was carried out with the support of a research grant from ISIS, Fujitsu Laboratories.     

Oxidation of some aliphatic polyols on anodically deposited MnO2

Galvanostatic steady state current potential measurements were carried out for oxidation of a series of aliphatic alcohols having varying number of hydroxyl groups. The anodically deposited layer of MnO₂ on platinum was used as the electrode material. The deposit was characterised by scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDAX) and electrode potential measurements. The catalytic role of MnO₂ in the electro-oxidation of alcohols was indicated by the chronopotentiograms and the cyclic voltammograms. An analysis of the electrochemical data indicated a catalytic EC mechanism in which Mn (V) is generated electrochemically and consumed chemically in succession. Based on this and the hydrogen bonding interaction between alcoholic hydroxyl groups and MnO₂ layer, a mechanism was proposed which accounts for the variation in the observed electrochemical reaction orders. Tafel behaviour was found to be followed only approximately. Current efficiency of the electrochemical oxidation of polyols was studied. Replacement of platinum by carbon as current collector was found to leave the electrocatalytic activity of the MnO₂ deposit practically unaltered.     

NMR studies of poly(2-hydroxy ethyl methacrylate-co-2-vinyl pyridine)

Copolymers of 2-hydroxy ethyl methacrylate-2-vinyl pyridine (H/V) of different composition were synthesized by free radical bulk polymerization using azobisisobutyronitrile (AIBN) as an initiator under nitrogen atmosphere. The copolymer compositions were calculated from ¹H NMR spectra. The reactivity ratios for H/V copolymers obtained from a linear Kelen-Tudos method (KT) and nonlinear error-in-variables method (EVM) are r_H = 0.50 ± 0.10, r_V = 1.04 ± 0.08 and r_H = 0.55, r_V = 1.06 respectively. The complete spectral assignment of methine, methylene, methyl, carbonyl, and aromatic carbon regions in term of compositional and configurational sequences of H/V copolymers were done with the help of ¹³C{¹H} NMR, distortionless enhancement by polarization transfer (DEPT), two-dimensional heteronuclear single quantum coherence (HSQC) along with total correlated spectroscopy (TOCSY). © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

A Maximum Likelihood Stereo Algorithm

A stereo algorithm is presented that optimizes a maximum likelihood cost function. The maximum likelihood cost function assumes that corresponding features in the left and right images are normally distributed about a common true value and consists of a weighted squared error term if two features are matched or a (fixed) cost if a feature is determined to be occluded. The stereo algorithm finds the set of correspondences that maximize the cost function subject to ordering and uniqueness constraints. The stereo algorithm is independent of the matching primitives. However, for the experiments described in this paper, matching is performed on the $cf4$individual pixel intensities.$cf3$ Contrary to popular belief, the pixel-based stereo appears to be robust for a variety of images. It also has the advantages of (i) providing adensedisparity map, (ii) requiringnofeature extraction, and (iii)avoidingthe adaptive windowing problem of area-based correlation methods. Because feature extraction and windowing are unnecessary, a very fast implementation is possible. Experimental results reveal that good stereo correspondences can be found using only ordering and uniqueness constraints, i.e., withoutlocalsmoothness constraints. However, it is shown that the original maximum likelihood stereo algorithm exhibits multiple global minima. The dynamic programming algorithm is guaranteed to find one, but not necessarily the same one for each epipolar scanline, causing erroneous correspondences which are visible as small local differences between neighboring scanlines. Traditionally, regularization, which modifies the original cost function, has been applied to the problem of multiple global minima. We developed several variants of the algorithm that avoid classical regularization while imposing several global cohesiveness constraints. We believe this is a novel approach that has the advantage of guaranteeing that solutions minimize the original cost function and preserve discontinuities. The constraints are based on minimizing the total number of horizontal and/or vertical discontinuities along and/or between adjacent epipolar lines, and local smoothing is avoided. Experiments reveal that minimizing the sum of the horizontal and vertical discontinuities provides the most accurate results. A high percentage of correct matches and very little smearing of depth discontinuities are obtained. An alternative to imposing cohesiveness constraints to reduce the correspondence ambiguities is to use more than two cameras. We therefore extend the two camera maximum likelihood toNcameras. TheN-camera stereo algorithm determines the “best” set of correspondences between a given pair of cameras, referred to as the principal cameras. Knowledge of the relative positions of the cameras allows the 3D point hypothesized by an assumed correspondence of two features in the principal pair to be projected onto the image plane of the remainingN− 2 cameras. TheseN− 2 points are then used to verify proposed matches. Not only does the algorithm explicitly model occlusion between features of the principal pair, but the possibility of occlusions in theN− 2 additional views is also modeled. Previous work did not model this occlusion process, the benefits and importance of which are experimentally verified. Like other multiframe stereo algorithms, the computational and memory costs of this approach increase linearly with each additional view. Experimental results are shown for two outdoor scenes. It is clearly demonstrated that the number of correspondence errors is significantly reduced as the number of views/cameras is increased.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

Densities and excess molar volumes of mixtures containing diesel,biodiesel and alkanols at temperatures from 288.15 to 313.15 K

The present work is focusing on the synthesization and physico-chemical properties of Jatropha curcas biodiesel with diesel and alcohols.The densities of binary diesel (2)+1-alkanols (C_3 or C_4)(3) and ternary Jatropha curcas biodiesel (1)+diesel (2)+1-alkanols (C_3or C_4)(3) blends have been reported over full range of composition at temperatures within range 288.15 to 313.15 K.Also densities of Jatropha curcas biodiesel (1)+diesel or 1-alkanols (C_3 or C_4)(2) blends have been measured at 313.15 K.Excess molar volumes,V~E,V~E_(123)of binary and ternary blends were calculated from the measured data and the derived properties were correlated to composition using Redlich–Kister equation.A reasonable agreement was found between the measured and estimated values.Further,densities and excess molar volumes data were reasoned to discuss molecular interactions taking into consideration effect of composition and temperature.     

Cover Feature: Superior Proton-Transfer Catalytic Promiscuity of Cytochrome c in Self-Organized Media (7/2021)

Evolutionarily elderly proteins commonly feature greater catalytic promiscuity. Cytochrome c is among the first set of proteins in evolution to have known prospects in electron transport and peroxidative properties. Here, we report that cyt c is also a proficient proton-transfer catalyst and enhances the Kemp elimination (KE; model reaction to show proton transfer catalytic property) by ∼750-fold on self-organized systems like micelles and vesicles. The self-organized systems mimic the mitochondrial environment in vitro for cyt c. Using an array of biophysical and biochemical mutational assays, both acid–base and redox mechanistic pathways have been explored. The histidine moiety close to hemin group (His18) is mainly responsible for proton abstraction to promote the concerted E2 pathway for KE catalysis when cyt c is in its oxidized form; this has also been confirmed by a H18A mutant of cyt c. However, the redox pathway is predominant under reducing conditions in the presence of dithiothreitol over the pH range 6–7.4. Interestingly, we found almost 750-fold enhanced KE catalysis by cyt c compared to aqueous buffer. Overall, in addition to providing mechanistic insights, the data reveal an unprecedented catalytic property of cyt c that could be of high importance in an evolutionary perspective considering its role in delineating the phylogenic tree and also towards generating programmable designer biocatalysts.