Aluminum dodecatungstophosphate (AlPW12O40) as an efficient heterogeneous inorganic catalyst for the chemoselective synthesis of geminal diacetates (acylals) under solvent-free conditions

An efficient and chemoselective preparation of acylals from structurally different aldehydes in the presence of AlPW₁₂O₄₀ and acetic anhydride was achieved easily in high yields at room temperature under solvent-free conditions.     

Determination of nanogram amounts of bromide and chloride by molecular emission cavity analysis based on gallium halide emission

By measuring the GaBr emission enhanced by iodide at 350 nm in a carbon cavity heated by a hydrogen/argon flame, 0–60 ng of bromide is determined with a detection limit of 0.5 ng μl^?1. In a similar way, gallium (0–20 ng) can be determined with a detection limit of 0.15 ng μl^?1. Interferences are reported. Chloride (0–1200 ng) is determined by means of GaCl emission; the detection limit is 50 ng μl^?1.     

Preferred design of recurrent neural network architecture using a multiobjective evolutionary algorithm with un-supervised information recruitment: a paradigm for modeling shape memory alloy actuators

Shape memory alloys (SMAs) are able to compensate any undergoing plastic deformations and return to their memorized shape. Such a behavior persuades industrialists to use them for different engineering applications, as smart actuators and sensors. Because of their vast applications, it is crucial to engineers to develop effective identification tools capable of simulating the behavior of SMAs. However, SMA actuators have complex and hysteric behavior that in turn obstructs the modeling process. The motivation behind the current study emanates in the pursuit of developing efficient prediction tools for effective modeling of SMA actuators. Actually, after several experiments and software simulations, the authors develop a hybrid intelligent tool which takes advantage of the self-organizing Pareto based evolutionary algorithm (SOPEA) and simultaneous recurrent neural network (SRNN), as a black-box model, to automatically identify the behavior of SMA. SOPEA is a multiobjective evolutionary algorithm which is based on the concepts of survival of the fittest, non-dominated sorting and information recruitment. The information recruitment is guaranteed by applying an un-supervised neuro computing technique, i.e. adaptive self organizing map (ASOM) with conscience mechanism. ASOM is an un-supervised network that assists SOPEA to recognize the non-dominated patterns and produce further non-dominated solutions. Together with the structure of SOPEA, the authors follow a comprehensive preference-based strategy to exploit the desired regions in the Pareto front. This occurs through introducing deliberate reference points. The outcome method is applied to the design of SRNN for modeling the SMA actuator. It is demonstrated that the designed optimization tool can show acceptable performance for the present case study within the imposed computational budget. Besides, through a rigorous experimental procedure, it is indicated that by applying an efficient artificial system, the behavior of SMA can be identified without any specific knowledge of the physical conditions and governing equations.     

Analysis of furanocoumarins from Yemenite Dorstenia species by liquid chromatography/electrospray tandem mass spectrometry

A series of prevailing prenylated furanocoumarins from leaves of Dorstenia gigas and Dorstenia foetida (Moraceae) were investigated by liquid chromatography/electrospray tandem mass spectrometry. The mass spectral behavior of the furanocoumarins under positive ion electrospray conditions is discussed using both an ion trap and a triple quadrupole system. It is demonstrated that both methods represent valuable tools not only for the rapid classification of this type of compounds, but also with respect to their substitution pattern. Copyright © 2012 John Wiley & Sons, Ltd.     

Plasmonic Bragg reflectors based on metal-embedded MIM structure

We propose and investigate a metalembedded metal-insulator-metal (MIM) structure plasmonic Bragg reflector (PBR) using the finite-difference time-domain (FDTD) method with PMLs (perfectly matched layers) boundary conditions. It improves the performance of conventional step profile MIM PBRs to some extent. Our numerical study reveals that the metal-embedded PBRs exhibit lower insertion loss, narrower bandgap, and reduced rippling in the transmission spectrum when compared with the step PBRs at the same normalized index contrast and transmission levels. The defect mode of the metal-embedded PBRs also exhibits higher transmission. To suppress the sidelobes in the transmission spectrum, we further smooth the end of the embedded metal, which demonstrates a better performance. Then, we find with respect to the Bragg wavelength, the longer wavelengths have a tendency to spread in the wider regions of the insulator layer; however, the shorter wavelengths have a tendency to spread in the embedded metal regions. The apodized PBRs with the embedded metal length decreasing (increasing) efficaciously suppress the ripples at the right (left) band edges. Then, we use the impedance theoretical model to explain this phenomenon. Finally, we realize a flat-top transmission band filter by connecting two apodized PBRs, and the band and center wavelength can be adjusted.     

Solvable systems of linear differential equations

The asymptotic iteration method (AIM) is an iterative technique used to find exact and approximate solutions to second-order linear differential equations. In this work, we employed AIM to solve systems of two first-order linear differential equations. The termination criteria of AIM will be re-examined and the whole theory is re-worked in order to fit this new application. As a result of our investigation, an interesting connection between the solution of linear systems and the solution of Riccati equations is established. Further, new classes of exactly solvable systems of linear differential equations with variable coefficients are obtained. The method discussed allow to construct many solvable classes through a simple procedure.     

Al Kα and Cu Kα1 excited XPS of vanadium oxide and VF3 powders: Measurement of the V 1s – KLL Auger parameters

Al Kα (hν = 1486.6 eV) excited XPS shows that powder samples of V₂O₃, V₂O₅ and VF₃ are surface contaminated and that the V₂O₃ can be cleaned by heating in vacuum at 400 °C. The greater sampling depth of Cu Kα₁ (hν = 8047.8 eV) excited XPS allows measurement of the bulk V 1s – KL₂L₃ Auger parameters (APs) for these materials. The APs of VF₃ and V₂O₅, relative to V metal, fall into the range of values expected for metal fluorides and oxides with non-local final state core-hole screening, whereas the AP of V₂O₃ is significantly closer to that of V metal. We ascribe this to a greater final state valence orbital occupation following photionisation in V₂O₃, part of which results from metal-like screening.