A new hybrid mutation operator for multiobjective optimization with differential evolution

Differential evolution has become one of the most widely used evolutionary algorithms in multiobjective optimization. Its linear mutation operator is a simple and powerful mechanism to generate trial vectors. However, the performance of the mutation operator can be improved by including a nonlinear part. In this paper, we propose a new hybrid mutation operator consisting of a polynomial-based operator with nonlinear curve tracking capabilities and the differential evolution’s original mutation operator, for the efficient handling of various interdependencies between decision variables. The resulting hybrid operator is straightforward to implement and can be used within most evolutionary algorithms. Particularly, it can be used as a replacement in all algorithms utilizing the original mutation operator of differential evolution. We demonstrate how the new hybrid operator can be used by incorporating it into MOEA/D, a winning evolutionary multiobjective algorithm in a recent competition. The usefulness of the hybrid operator is demonstrated with extensive numerical experiments showing improvements in performance compared with the previous state of the art.     

Porous nickel telluride nanostructures as bifunctional electrocatalyst towards hydrogen and oxygen evolution reaction

Electrochemical water splitting technology has attracted researchers for the development of next generation fuels. Herein, we report the synthesis of nanostructured porous hollow nickel telluride nanosheets and their use as bifunctional electrocatalyst towards hydrogen and oxygen evolution reaction, anticipating an enhanced performance owing to their 2D sheet like morphology, conductivity, porous nature providing larger catalytic surface for water splitting reaction. In this regard, nickel telluride nanostructures were synthesized via an anion-exchange-reaction between pre-synthesized nickel hydroxide hexagonal nanosheets and tellurium ions under hydrothermal conditions. The as-synthesized nanostructures were characterized for structural, morphological and compositional properties using X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, high resolution transmission electron microscopy and energy dispersive X-ray spectroscopy. Nickel telluride modified electrodes were tested as bifunctional electrocatalyst under acidic and alkaline conditions, through linear sweep voltammetry and constant current chronopotentiometry methods. The modified electrodes revealed an onset potential of ?422 mV and 87.4 mV dec^?1 Tafel slope towards HER and overpotential of 679 mV and 151 mV dec^?1 Tafel slope towards OER. The lower onset potentials are complimented with excellent electrocatalytic stability.     

Moisture diffusion through nanoclay/vinylester processed using twin‐screw extrusion

This research concerns moisture absorption through nanoclay/vinylester composites in artificial seawater medium and the resulting properties of degradation. Cloisite 15A, an organomodified nanoclay, and Cloisite Na, a naturally occurring nanoclay, were studied to examine the influence of organomodification on the moisture ingress behavior of the nanocomposites processed by using ultrasonication and twin‐screw extrusion. Although X‐ray diffraction and transmission electron microscopy analysis revealed exfoliation of Cloisite 15A in vinylester, Cloisite Na was only intercalated. Moisture diffusivity decreased by 72% due to the addition of 5 wt% of Cloisite 15A to vinylester. However, the same increased in the case of the addition of Cloisite Na, suggesting a positive influence of the organomodification on the moisture barrier properties. Although Fick's Law of Diffusion showed deviation from the experimental data in the nonlinear region of moisture absorption as a function of duration of exposure, the Langmuir Model was in better agreement with the experimental data in the entire range. (Cloisite 15A)/vinylester showed lower levels of microhardness deterioration due to moisture absorption than that of (Cloisite Na)/vinylester. J. VINYL ADDIT. TECHNOL., 20:152–159, 2014. © 2014 Society of Plastics Engineers     

A novel approach for the biosynthesis of silver oxide nanoparticles using aqueous leaf extract of Callistemon lanceolatus (Myrtaceae) and their therapeutic potential

This study describes a novel biological route for the biosynthesis of silver oxide nanoparticles utilising the aqueous extract of Callistemon lanceolatus D.C. leaves. Formation of silver oxide nanoparticles was confirmed by UV–visible spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscope–energy dispersive X-ray spectroscopy and X-ray diffraction spectroscopy analysis. The biologically synthesised silver oxide nanoparticles were found to be 3–30 nm in size with spherical and hexagonal shape by high-resolution transmission electron microscope analysis. Furthermore, the biogenic silver oxide nanoparticles demonstrated significant (p?in vitro antioxidant methods. These particles also exhibited significant (p?相似文献   

Finite Element Approach for Failure Analysis of a Gas Turbine Blade

Journal of Failure Analysis and Prevention - In the present work, a case study on the gas turbine blade is undertaken for failure analysis through finite element approach. The analysis is carried...     

Liquid Crystals with Interfacial Ordering that Enhances Responsiveness to Chemical Targets

The development of stimuli‐responsive materials suitable for use in wearable sensors is a key unresolved challenge. Liquid crystals (LCs) are particularly promising, as they do not require power, are light‐weight, and can be tuned to respond to a range of targeted chemical stimuli. Here, an advance is reported in the design of LCs for chemical sensors with the discovery of LCs that assume parallel orientations at free surfaces and yet retain their chemoresponsiveness. The resulting LC‐based sensors are more sensitive and exhibit faster responses than previous LC sensor designs.     

Optimisation of turning parameters by integrating genetic algorithm with support vector regression and artificial neural networks

This paper focuses on optimisation of process parameters of the turning operation, using artificial intelligence techniques such as support vector regression (SVR) and artificial neural networks (ANN) integrated with genetic algorithm (GA). The model is trained using the turning parameters as the input and corresponding surface roughness, tool wear and power required as the output. Data, obtained from conducting experiments is analysed using support vector machine (SVM) and artificial neural network. SVM, a nonlinear model, is learned by linear learning machine by mapping into high-dimensional kernel-induced feature space. The genetic algorithm is integrated with these to find the optimum from the response surface generated. The results are compared with those obtained by integrating GA with traditional models like response surface methodology (RSM) and regression analysis (RA). This paper illustrates the impact that techniques based on artificial intelligence have on optimising processes.     

Abiotic reductive dechlorination of cis-dichloroethylene by Fe species formed during iron- or sulfate-reduction

This study investigated reductive dechlorination of cis-dichloroethylene (cis-DCE) by the reduced Fe phases obtained from in situ precipitation, which involved mixing of Fe(II), Fe(III), and S(-II) solutions. A range of redox conditions were simulated by varying the ratio of initial Fe(II) concentration ([Fe(II)](o)) to initial Fe(III) concentration ([Fe(III)](o)) for iron-reducing conditions (IRC) and the ratio of [Fe(II)](o) to initial sulfide concentration ([S(-II)](o)) for sulfate-reducing conditions (SRC). Significant dechlorination of cis-DCE occurred under highly reducing IRC and iron-rich SRC, suggesting that Fe (oxyhydr)oxides including green rusts are highly reactive with cis-DCE but that Fe sulfide as mackinawite (FeS) is nonreactive. Relative concentrations of sulfate to chloride were also varied to examine the anion impact on cis-DCE dechlorination. Generally, slower dechlorination occurred in the batches with higher sulfate concentrations. As indicated by higher dissolved Fe concentration, the slower dechlorination in the presence of sulfate was probably due to the decreased surface-complexed Fe(II). This study demonstrates that the chemical form of reduced Fe(II) is critical in determining the fate of cis-DCE under anoxic conditions.