Reaching for two new stable ambiphilic quinoline‐derived N‐heterocyclic carbenes at DFT level

A detailed investigation on the thermodynamic and kinetic stability of four carbenic tautomers of quinoline 1 , including quinoline‐2‐ylidene 2 , quinoline‐3‐ylidene 3 , quinoline‐4‐ylidene 4 , and 3,4‐dihydroquinoline‐4‐ylidene 5 , reveals that singlet planar six‐membered ring N‐heterocyclic carbenes (NHCs) 2 and 4 have less stability than Arduengo type NHC but seems to have enough conceivably for reaching at B3LYP/aug‐cc‐pVTZ//B3LYP/6–31+G* and B3LYP/6–311++G**//B3LYP/6–31+G* levels. All these six‐membered NHCs are extremely ambiphilic with the more nucleophilic and electrophilic characters compared to the Arduengo type one. The aromaticity of singlet 2 and 4 is a significant contributor to their stability which is confirmed through their Nucleus‐independent chemical shift(1)_zz values. Finally, among 2–5 , the normal NHC 2 is thermodynamically preferred but the remote NHC 4 is kinetically proffered over the other isomeric carbenes. The effects of different N‐ or C‐substituted NHCs of 2 are studied using appropriate isodesmic reactions. The trimethylsilyl substituent exhibits slightly larger carbene stabilization in quinoline‐derived NHCs than the pyridine analogue. © 2014 Wiley Periodicals, Inc.     

Optimal economic load dispatch based on wind energy and risk constrains through an intelligent algorithm

This article focus on optimal economic load dispatch based on an intelligent method of shark smell optimization (SSO). In this problem, the risk constrains has been considered which has root in uncertainity and unpredictable behavior of wind power. Regarding to increasing of this clean energy in power systems and un‐dispatchable behavior of wind power, its conditional value at risk index considered in this article which consists of loss from load and "spilling" wind energy connected with unpredictable imbalances among generation and load. This problem has been considered as an optimization problem based on SSO that evaluate the balance between cost and risk. This algorithm is based on distinct shark smell abilities for localizing the prey. In sharks' movement, the concentration of the odor is an important factor to guide the shark to the prey. In other words, the shark moves in the way with higher odor concentration. This characteristic is used in the proposed SSO algorithm to find the solution of an optimization problem. Effectiveness of the proposed method has been applied over 30‐bus power system in comparison with other techniques. © 2016 Wiley Periodicals, Inc. Complexity 21: 494–506, 2016     

Nano-Co-[4-chlorophenyl-salicylaldimine-pyranopyrimidine dione]Cl2 as a new Schiff base complex and catalyst for the one-pot synthesis of some 4H-pyrimido[2,1-b]benzazoles

Research on Chemical Intermediates - Nano-Co-[4-clolorophenyl-salsylaldimine-pyranopyrimidine dione]Cl2 {Nano-[Co-4CSP]Cl2} was prepared and fully characterized as a new nano-Schiff base complex....     

A new method for probabilistic assessments in power systems,combining monte carlo and stochastic‐algebraic methods

This article discusses a new methodology, which combines two efficient methods known as Monte Carlo (MC) and Stochastic‐algebraic (SA) methods for stochastic analyses and probabilistic assessments in electric power systems. The main idea is to use the advantages of each former method to cover the blind spots of the other. This new method is more efficient and more accurate than SA method and also faster than MC method while is less dependent of the sampling process. In this article, the proposed method and two other ones are used to obtain the probability density function of different variables in a power system. Different examples are studied to show the effectiveness of the hybrid method. The results of the proposed method are compared to the ones obtained using the MC and SA methods. © 2014 Wiley Periodicals, Inc. Complexity 21: 100–110, 2015     

Day‐ahead price forecasting based on hybrid prediction model

Short‐Term Price Forecast is a key issue for operation of both regulated power systems and electricity markets. Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, nonstationary, and time variant behavior of electricity price time series. So, in this article, the forecast model includes wavelet transform, autoregressive integrated moving average, and radial basis function neural networks (RBFN) is presented. Also, an intelligent algorithm is applied to optimize the RBFN structure, which adapts it to the specified training set, reduce computational complexity and avoids over fitting. Effectiveness of the proposed method is applied for price forecasting of electricity market of mainland Spain and its results are compared with the results of several other price forecast methods. These comparisons confirm the validity of the developed approach. © 2016 Wiley Periodicals, Inc. Complexity 21: 156–164, 2016     

Synthesis of nanostructural Yttrium fluorosilicate glass ceramic via sol–gel method

Journal of Sol-Gel Science and Technology - The yttrium fluorosilicate glass ceramic pieces were prepared by sol–gel method starting from yttrium acetate, trifluoroacetic acid, and...     

Synthesis of Core-Shell Magnetic Supramolecular Nanocatalysts based on Amino-Functionalized Calix[4]arenes for the Synthesis of 4H-Chromenes by Ultrasonic Waves

One of the most common phenol-formaldehyde cyclic oligomers from hydroxyalkylation reactions that exhibit supramolecular chemistry are calixarenes. These macrocyclic compounds are qualified to act as synthetic catalysts due to their specific features including being able to form host-guest complexes, having unique structural scaffolds and their relative ease of chemical modifications with a variety of functions on their upper rim and lower rim. Here, a functional magnetic nanocatalyst was designed and synthesized by using a synthetic amino-functionalized calix[4]arene. Its catalytic activity was evaluated in a one-pot synthesis of 2-amino-4H-chromene derivatives. Besides, this novel magnetic nanocatalyst was characterized by spectroscopic and analytical techniques such as FT-IR, EDX, FE-SEM, TEM VSM, XRD analysis.     

Rapid green synthesis of gold nanoparticles using Rosa hybrida petal extract at room temperature

This study reports a green method for the synthesis of gold nanoparticles using the aqueous extract of rose petals. The effects of gold salt concentration, extract concentration and extract quantity were investigated on nanoparticles synthesis. Gold nanoparticles were characterized with different techniques such as UV-vis spectroscopy, FT-IR spectroscopy, X-ray diffraction, energy dispersive X-ray spectroscopy, dynamic light scattering and transmission electron microscopy. Transmission electron microscopy experiments showed that these nanoparticles are formed with various shapes. FT-IR spectroscopy revealed that gold nanoparticles were functionalized with biomolecules that have primary amine group (-NH2), carbonyl group, -OH groups and other stabilizing functional groups. X-ray diffraction pattern showed high purity and face centered cubic structure of gold nanoparticles. Dynamic light scattering technique was used for particle size measurement, and it was found to be about 10nm. The rate of the reaction was high and it was completed within 5 min.