Thin-film iron-oxide nanobeads as bifunctional electrocatalyst for high activity overall water splitting

Developing only Fe derived bifunctional overall water splitting electrocatalyst both for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) while performing at low onset overpotential and with high catalytic stability is a rare instance. We present here the first demonstration of unique iron-oxide nanobeads (FeO_x-NBs) based electrocatalyst executing both OER and HER with high activity. Thin-film electrocatalytic FeO_x-NBs assembly is surface grown via simple spray coating (SC). The unique SC/FeO_x-NBs propels OER initiating water oxidation just at 1.49 V_RHE (η = 260 mV) that is the lowest observable onset potential for OER on simple Fe-oxide based catalytic films reported so far. Catalyst also reveals decently high HER activity and competent overall water splitting performance in the FeO_x-NBs two-electrode system as well. Catalyst also presents stable kinetics, with promising high electrochemically active surface area (ECSA) of 1765 cm², notable Tafel slopes of just 54 mV dec^1? (OER) and 85 mV dec^1? (HER), high exchange current density of 1.10 mA cm^2? (OER), 0.58 mA cm^2? (HER) and TOF of 74.29s^1?@1.58V_RHE, 262s^1?@1.62V_RHE (OER) and 82.5s^1?@-0.45V_RHE, 681s^1?@-0.56V_RHE (HER).     

Coherent control of symmetric and asymmetric diffraction grating via relative phase

ABSTRACT

We present a theoretical model to realize the symmetric and asymmetric diffraction grating in a four-level atomic medium. The proposed atomic medium follows a double lambda configuration where four fields interact with it. We get control over symmetric and asymmetric behavior of the diffraction grating by manipulating the relative phase of the fields. Interestingly, the symmetric and asymmetric diffraction grating become prominent when the vortex beam is used instead of the plane wave. Enhanced first, second, and third-order diffraction gratings are achieved via the vortex beam. Further, we find control over asymmetric diffraction gratings by the relative phase of the fields. Coherent control of asymmetric diffraction grating in negative and positive diffracted angles is also achieved via the relative phase.     

Investigation of Dissipation,Adsorption, Degradation,and Leaching of Triazophos Pesticide in Various Soils

This study concerns the investigation of dissipation, adsorption, and degradation of triazophos in different soils from Pakistan. These processes help in the disappearance of pesticide from the environment. Gas chromatography was used for dissipation and adsorption analysis while for degradation study mass spectrometer was used in addition of gas chromatography (GC-MS). The dissipation rate of triazophos in three different soils was 90% over 30 days with average half-life of 9.059 days. From dissipation study it was inferred that rate is variable in each soil due to climatic changes, soil nature and soil-pesticide interactions. Adsorption experiment has revealed that the adsorption of this pesticide to soil follows the pseudo first order kinetic model with rate constant value of 0.479/h and Freundlich isotherm with adsorption capacity of 1.832 mol/g. Degradation study has displayed two major metabolites, one is phosphorothioic acid, S-[2-[(1-cyano-1-methylethyl) amino]-2-oxoethyl] O,O-diethyl ester at retention time of 9.136 and the other is sulfotep at 14.304 min. The leaching potential of triazophos was also calculated from its half-life and organic carbon content present in soil which was 1.688 representing it as non leacher pesticide.     

Meta-learning for evolutionary parameter optimization of classifiers

The performance of most of the classification algorithms on a particular dataset is highly dependent on the learning parameters used for training them. Different approaches like grid search or genetic algorithms are frequently employed to find suitable parameter values for a given dataset. Grid search has the advantage of finding more accurate solutions in general at the cost of higher computation time. Genetic algorithms, on the other hand, are able to find good solutions in less time, but the accuracy of these solutions is usually lower than those of grid search.     

A multi‐objective evolutionary optimization of fuzzy controller for energy conservation in air conditioning systems

This paper presents the use of evolutionary optimization approach to design and tune smart fuzzy controllers for heating, ventilation, and air conditioning systems or HVAC. The objective is to optimize energy consumption while accounting for user comfort requirements. The problem of energy conservation in air conditioning systems becomes a multi‐objective optimization constrained problem, which enlarges the solution search space. To solve this problem, a multi‐objective evolutionary optimization technique based on genetic algorithm (GA) is proposed. A physical experimental setup is constructed for data collection and formulation of mathematical model. A fuzzy controller is initially designed through expert knowledge, and GA is then used to tune the rules and membership functions of the fuzzy controller in order to optimize multiple objectives. Simulations and real experiments are compared to determine the effectiveness of the proposed strategy. As compared to the controller present in the real experimental air conditioner, approximately 15% energy is successfully saved with no increase in average individual dissatisfaction or discomfort index. Also, a decrease in peak individual dissatisfaction or discomfort index from 91% to 62% is observed. Copyright © 2013 John Wiley & Sons, Ltd.