NiO/Porous Reduced Graphene Oxide as Active Hybrid Electrocatalyst for Oxygen Evolution Reaction

Russian Journal of Electrochemistry - At present, the graphene hybrid as electrode material demonstrates the efficient performance for oxygen evolution reaction (OER). OER influences some important...     

Phosphine-free conversion of alcohols into alkyl thiocyanates using trichloroisocyanuric acid/NH4SCN

A convenient and efficient phosphine-free procedure for the one-pot conversion of primary,secondary and tertiary alcohols into the corresponding alkyl thiocyanates or alkyl isothiocyanates is described using trichloroisocyanuric acid/NHUSCN.     

Forecasting of water thermal conductivity enhancement by adding nano-sized alumina particles

Operating fluids play an important role in heat transfer equipment. Water is inexpensive popular operating fluid with extensive applications, but its thermophysical properties are not good enough, especially for high temperature processes. Therefore, modification of its inherent characteristics by adding nano-sized solid particles found high popularities. Thermal conductivity is one of the most important thermophysical properties of an operating fluid in relatively all energy-based processes. Variation of thermal conductivity of nanofluids with different operating conditions is required to be understood in such processes. Therefore, the focus of this study is concentrated on modeling of thermal conductivity of water-alumina nanofluids using four different smart paradigms. Multilayer perceptron, radial basis function, cascade feedforward, and generalized regression neural networks are employed for the considered task. The best structure of these paradigms is determined, and then, their accuracies are compared using different statistical indices. Accuracy analyses confirmed that the generalized regression neural network outperforms other considered smart methodologies. It predicted more than 280 experimental datasets with excellent absolute average relative deviation?=?0.71%, mean square error?=?0.0006, root mean square error?=?0.023 and regression coefficient (R²)?=?0.9675. In the final stage, the proposed paradigm is used for investigation of the effect of influential parameters on the thermal conductivity of water-alumina nanofluids. This type of accurate and straightforward paradigm can broaden our insight about thermal behavior of homogeneous suspension of nano-size alumina particles in water.

     

A new analytical definition of the dead material zone for forward extrusion of shaped sections

This article aims to provide a new formulation for the analysis of the extrusion process for non-axisymmetric sections. The upper bound theorem has been used to obtain a generalized kinematically admissible velocity field. The geometry of the deforming region has been formulated considering variation of the dead zone size at different angular positions and three-dimensional curved surfaces have been employed to define the entry and exit surfaces of the deformation zone. Using this analytical method, extrusion of square, rectangular and L-shaped sections were analyzed and the effect of shape complexity on material flow and dead material zone (DMZ) formation under different conditions has been investigated. Physical modelling experiments and finite element analysis were carried out to reveal the capability of the proposed theoretical method.     

Cyclically Presented Modules Over Rings of Finite Type

A ring is of finite type if it has only finitely many maximal right ideals, all two-sided. In this article, we give a complete set of invariants for finite direct sums of cyclically presented modules over a ring R of finite type. More generally, our results apply to finite direct sums of direct summands of cyclically presented right R-modules (DCP modules). Using a duality, we obtain as an application a similar set of invariants for kernels of morphisms between finite direct sums of pair-wise non-isomorphic indecomposable injective modules over an arbitrary ring. This application motivates the study of DCP modules.     

A microwave-assisted solvent- and catalyst-free synthesis of aminomethylene bisphosphonates

A convenient preparative approach for the synthesis of aminomethylene bisphosphonates is developed which involves treatment of amines with triethyl orthoformate and diethyl phosphite under microwave irradiation.     

Swarm contours: A fast self‐organization approach for snake initialization

A major obstacle in real‐time performance of a visual tracking system is its initialization phase. Inspired by social behavior in fish and ant groups, a fast self‐organization approach to active‐contour initialization is proposed. Contours are emerged during two separate phases of aggregation and self‐assembly. Aggregation is achieved by a superposition of simpler behaviors, hunting, avoidance, and opportunism. Self‐assembly, which constitutes the explicit contour formation, occurs by mating behavior when the swarm becomes quite stable. Experiments indicate that the proposed method outperforms exhaustive image search for finding contours in high resolutions. © 2006 Wiley Periodicals, Inc. Complexity 12: 41–52, 2006     

Application of honey-bee mating optimization algorithm on clustering

Cluster analysis is one of attractive data mining technique that use in many fields. One popular class of data clustering algorithms is the center based clustering algorithm. K-means used as a popular clustering method due to its simplicity and high speed in clustering large datasets. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. Over the last decade, modeling the behavior of social insects, such as ants and bees, for the purpose of search and problem solving has been the context of the emerging area of swarm intelligence. Honey-bees are among the most closely studied social insects. Honey-bee mating may also be considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of marriage in real honey-bee. Honey-bee has been used to model agent-based systems. In this paper, we proposed application of honeybee mating optimization in clustering (HBMK-means). We compared HBMK-means with other heuristics algorithm in clustering, such as GA, SA, TS, and ACO, by implementing them on several well-known datasets. Our finding shows that the proposed algorithm works than the best one.     

Selective fluorination of m-tyrosine by OF2

Fluorine-18 labeled aromatic amino acids are routinely used as tracers in positron emission tomography (PET) to study in vivo metabolic processes. The most versatile method for the production of such radiotracers is electrophilic fluorination of the aromatic amino acid with [¹⁸F]F₂, which is most commonly produced by the gas-phase nuclear reaction ¹⁸O(p, n)¹⁸F. Although [¹⁸F]F₂ is the major product, considerable amounts of [¹⁸F]OF₂ (up to 20%) are also produced. Electrophilic fluorination reactions of l-phenylalanine, 3-nitro-l-tyrosine, 4-nitro-dl-phenylalanine, 3,4-dihydroxyphenyl-l-alanine (l-DOPA), 3-O-methyl-l-DOPA, 3,4-dimethoxy-l-phenylalanine, p-tyrosine and o-tyrosine in H₂O and of m-tyrosine in anhydrous HF (aHF), CF₃SO₃H, CF₃COOH, CH₃COOH, HCOOH and H₂O using OF₂ were investigated. Although F₂ is an efficient fluorinating agent in aHF, electrophilic fluorination reactions using OF₂ were shown to be most efficient in less acidic media such as H₂O. In addition, and contrary to reports that OF₂ and F₂ have similar reactivities, m-tyrosine was the only aromatic system studied that was fluorinated by OF₂ and this was optimum in H₂O for the fluorinated m-tyrosine isomers (total yield, 4.35 ± 0.04%). The presence of [¹⁸F]OF₂ byproduct has no significant impact on the fluorination of aromatic amino acids investigated in this study and the subsequent production of their corresponding ¹⁸F-labeled radiotracers for patient use.