γ-Al2O3-Supported 12-Tungstosilicic Acid as an Efficient Heterogeneous Catalyst for the Synthesis of α-Aminonitrile

The multicomponent Strecker reaction using trimethylsilyle cyanide was performed in very short reaction times, and α-aminonitriles were prepared in excellent yields in the presence of a catalytic amount of alumina-supported tungstosilicic acid.     

Experimental Investigation of Mixed Convection in a Channel With an Open Cavity

Mixed convection in an open cavity with a heated wall bounded by a horizontally unheated plate is investigated experimentally. The cavity has the heated wall on the inflow side. Mixed convection fluid flow and heat transfer within the cavity is governed by the buoyancy parameter, Richardson number (Ri), and Reynolds number (Re). The results are reported in terms of wall temperature profiles of the heated wall and flow visualization for Re = 100 and 1000, Ri in the range 30–110 (for Re = 1000) and 2800–8700 (for Re = 100), the ratio of the length to the height of cavity (L/D) is in the range 0.5–1.5, and the ratio of the channel height to cavity height (H/D) is in the range of 0.5 and 1.0. The present results show that the maximum dimensional temperature rise values decrease as the Reynolds and the Richardson numbers decrease. The flow visualization points out that for Re = 1000 there are two nearly distinct fluid motions: a parallel forced flow in the channel and a recirculation flow inside the cavity. For Re = 100 the effect of a stronger buoyancy determines a penetration of thermal plume from the heated plate wall into the upper channel. Nusselt numbers increase when L/D increase in the considered range of Richardson numbers.     

Influence of Y2Cu2O5 nanoparticles doping on superconducting properties of YBa2Cu3O7-δ

ABSTRACT

The blue phase of YBa₂Cu₃O_{7- δ} (YBCO) family, Y₂Cu₂O₅ (Y202) nanoparticles were prepared and doped into (YBCO) superconductor and the effect of doping on critical current density and critical temperature was investigated. Y202 nanoparticles with particle sizes of 47, 107 and 206?nm were prepared by a sol–gel combustion method and added into the YBCO superconductor by 0.5–2?wt.%. XRD and scanning electron microscope measurements were used to characterize the samples. The measurement of critical current density at 77?K revealed that the doped superconductors had larger critical current density compared to the undoped superconductors. For a fixed dopant concentration, by increasing the size of nanoparticles, the J_c was increased. For the samples including 0.5?wt.% of nanoadditives, J_c was higher. The highest critical current density of 137?A/cm² was measured for the superconductors containing 0.5?wt.% of 206?nm Y202 nanoparticles. Also, by increasing the nanoparticles concentration, the T_c was reduced.     

Estimating complicated baselines in analytical signals using the iterative training of Bayesian regularized artificial neural networks

The present work deals with the development of a new baseline correction method based on the comparative learning capabilities of artificial neural networks. The developed method uses the Bayes probability theorem for prevention of the occurrence of the over-fitting and finding a generalized baseline. The developed method has been applied on simulated and real metabolomic gas-chromatography (GC) and Raman data sets. The results revealed that the proposed method can be used to handle different types of baselines with cave, convex, curvelinear, triangular and sinusoidal patterns. For further evaluation of the performances of this method, it has been compared with benchmarking baseline correction methods such as corner-cutting (CC), morphological weighted penalized least squares (MPLS), adaptive iteratively-reweighted penalized least squares (airPLS) and iterative polynomial fitting (iPF). In order to compare the methods, the projected difference resolution (PDR) criterion has been calculated for the data before and after the baseline correction procedure. The calculated values of PDR after the baseline correction using iBRANN, airPLS, MPLS, iPF and CC algorithms for the GC metabolomic data were 4.18, 3.64, 3.88, 1.88 and 3.08, respectively. The obtained results in this work demonstrated that the developed iterative Bayesian regularized neural network (iBRANN) method in this work thoroughly detects the baselines and is superior over the CC, MPLS, airPLS and iPF techniques. A graphical user interface has been developed for the suggested algorithm and can be used for easy implementation of the iBRANN algorithm for the correction of different chromatography, NMR and Raman data sets.     

A column generation approach for aircraft sequencing problems: a computational study

This paper investigates the computational tractability of aircraft sequencing problems over multiple runways under mixed mode operations, contrasting an enhanced mixed-integer programme (MIP) and an accelerated column generation approach. First, we examine the benefit of augmenting a base MIP with valid inequalities, preprocessing routines, and symmetry-defeating hierarchical constraints in order to improve the performance of branch-and-bound (B&B)/cut techniques as implemented in commercial solvers. Second, we alternatively reformulate the problem as a set partitioning model that prompts the development of a specialized column generation approach. The latter is accelerated by incorporating an interior point dual stabilization scheme and a complementary column generation routine. Empirical results using a set of new, computationally challenging instances and classical instances in the OR Library reveal the potential and limitations of the two methodologies.     

Fischer-Tropsch Reaction Kinetics of Cobalt Catalyst in Supercritical Phase

Fischer-Tropsch synthesis under supercritical phase condition was examined in a continuous and a high-pressure fixed bed reactor by employing a cobalt catalyst (Co-R.Ru/γ-Al2O3). An integral reactor model involving Fischer-Tropsch reaction kinetics in the supercritical fluid n-hexane was used to describe the overall performance. On the basis of Langmuir-Hinshelwood-Hougen-Watson (LHHW) model, the reaction rate constants were obtained for the rate equations of CO conversion to CH4 formation under supercritical conditions.     

An informatics search for the low-molecular weight chromium-binding peptide

Background  

The amino acid composition of a low molecular weight chromium binding peptide (LMWCr), isolated from bovine liver, is reportedly E:G:C:D::4:2:2:2, though its sequence has not been discovered. There is some controversy surrounding the exact biochemical forms and the action of Cr(III) in biological systems; the topic has been the subject of many experimental reports and continues to be investigated. Clarification of Cr-protein interactions will further understanding Cr(III) biochemistry and provide a basis for novel therapies based on metallocomplexes or small molecules.