Preparation of sodium dimolybdate by the pyrolysis of sodium oxomolybdenum (VI) oxalate

Thermal studies on various oxalato complexes have been of immense interest as they yield finely divided, highly reactive oxides which are usually obtained at a much lower temperature than that required in the conventional method of preparation, i.e., heating a mixture of two or more constituents [1]. A survey of the literature reveals that the compounds having the general formula A₂[Mo₂O₅(C₂O₄)₂(H₂O)₂], where A = K⁺, NH⁺₄[2] and A = Cs⁺ [3], have been prepared and their thermal decomposition is studied, but no such information is available regarding the preparation and characterisation of Na₂[Mo₂O₅(C₂O₄)₂(H₂O)₂] (SMO), which forms the subject of study of this paper. Sodium dimolybdate (Na₂Mo₂O₇), the decomposition product of SMO, is obtained at 280°C, a temperature much lower than that required in the conventional method of preparation of heating a mixture of Na₂MoO₄ and MoO₃ [4].     

Lanthanoid metal nitrates with hydrogen bonded hexamethylenetetramine

Cerium, praseodymium, and neodymium nitrate complexes with hydrogen bonded hexamethylenetetramine (HMTA) of the formula [Ce(NO₃)₂(H₂O)₅](HMTA)₂(NO₃)(H₂O)₃, [Pr(NO₃)₂(H₂O)₆]₂[Pr(H₂O)₉](HMTA)₆(NO₃)₆(H₂O)₄ and [Nd(NO₃)₂(H₂O)₅](HMTA)₂(NO₃)(H₂O)₃ have been prepared and characterized by X-ray crystallography. All the complexes belong to monoclinic crystal system. Ce and Nd complexes have P21/n space group, whereas Pr complex has C2/c. Thermal analyses of these complexes were carried out using TG, DSC, which showed their multi-step decomposition. Kinetics of thermolysis has been done by applying model fitting as well as model free isoconversional method. In order to see the response of rapid heating, ignition delay measurements were carried out. The thermal decomposition pathways have also been demonstrated. On the basis of thermal studies the thermal stability of the complexes was found in the order; Pr > Ce > Nd. In order to identify the end products of thermolyses, X-ray diffraction patterns of end product were carried out which showed the formation of corresponding metal oxides.     

Sequence Analysis of KpnI Repeat Sequences to Revisit the Phylogeny of the Genus Carthamus L.

Repetitive DNA sequences constitute a significant proportion of eukaryotic genomes. Knowledge about the distribution of repetitive DNA sequences is necessary in order to gain insights into the organization, evolution and behavior of eukaryotic genomes. Therefore, we used two repetitive DNA sequences pCtKpnI-I and pCtKpnI-II, earlier reported in Carthamus tinctorius L. to study the phylogeny and to revise the taxonomic status of the taxa belonging to the genus. The study unraveled two major lines within the genus Carthamus; one line included all the diploid taxa (2n?=?24) and the other line comprised the taxa with 2n?=?20 and the polyploid taxa (2n?=?44 and 64). The results of the present study will prove useful in molecular breeding for improving some targeted agronomic traits in genus Carthamus.     

Structure of short polymers at interfaces: a combined simulation and theoretical study

The structure of polymers confined between surfaces is studied using computer simulation and a density functional approach. The simple model system considers the polymer molecule as a pearl necklace of freely jointed hard spheres, having attractions among the beads, confined between attractive surfaces. This approach uses the universality of the free-energy functional to obtain the self-consistent field required in the single chain simulation. The second-order direct correlation function for the uniform bulk fluid required as input has been calculated from the reference interaction site model integral equation theory using mean spherical approximation. The theoretical results are shown to compare well with the Monte Carlo simulation results for varying densities, chain lengths, and with different attractive interaction parameters. The simulation results on the conformational properties give important indications regarding the behavior of chains as they approach the surfaces.     

Complex permittivity,complex permeability and microwave absorption properties of ferrite–polymer composites

The complex permittivity (ε′–jε″), complex permeability (μ′–jμ″) and microwave absorption properties of ferrite–polymer composites prepared with different ferrite ratios of 50%, 60%, 70% and 80% in polyurethane (PU) matrix have been investigated in X-band (8.2–12.4 GHz) frequency range. The M-type hexaferrite composition BaCo⁺²_0.9Fe⁺²_0.05Si⁺⁴_0.95Fe⁺³_10.1O₁₉ was prepared by solid-state reaction technique, whereas commercial PU was used to prepare the composites. At higher GHz frequencies, ferrite's permeabilities are drastically reduced, however, the forced conversion of Fe⁺³ to Fe⁺² ions that involves electron hopping, could have increased the dielectric losses in the chosen composition. We have measured complex permittivity and permeability using a vector network analyzer (HP/Agilent model PNA E8364B) and software module 85071. All the parameters ε′, ε″, μ′ and μ″ are found to increase with increased ferrite contents. Measured values of these parameters were used to determine the reflection loss at various sample thicknesses, based on a model of a single-layered plane wave absorber backed by a perfect conductor. The composite with 80% ferrite content has shown a minimum reflection loss of −24.5 dB (>99% power absorption) at 12 GHz with the −20 dB bandwidth over the extended frequency range of 11–13 GHz for an absorber thickness of 1.6 mm. The prepared composites can fruitfully be utilized for suppression of electromagnetic interference (EMI) and reduction of radar signatures (stealth technology).     

Amperometric immunosensor for the detection of Vibrio cholerae O1 using disposable screen-printed electrodes.

A disposable amperometric immunosensor was studied for the rapid detection of Vibrio cholerae (V. cholerae), the causative agent of cholera, employing an indirect sandwich enzyme linked immunosorbent assay (ELISA) principle. Screen-printed electrodes (SPEs) were fabricated (by using commercial and homemade carbon inks), electrochemically characterized and the assay conditions were optimized for capturing antibodies and antigen. Whole cell lysate (WCL) of V. cholerae was used to raise antibodies in rabbits and mice. The antibodies raised against WCL of V. cholerae were found to be specific, and no cross reactivity was observed with other enteric bacteria. 1-Naphthyl phosphate was used as a substrate with the amperometric detection of its enzymatic hydrolysis product 1-naphthol at a potential of +400 mV vs. Ag/AgCl reference electrode. A comparison between the amperometric detection technique and the standard ELISA was made in terms of the total assay time, the amount of biological materials used and the sensitivity of detection. The minimum detection limit of the amperometric immunosensor for V. cholerae was found to be 10(5) cells/ml in 55 min, while ELISA detected 10(6) cells/ml in 4 h.     

A Class of stochastic programs with decision dependent uncertainty

We address a class of problems where decisions have to be optimized over a time horizon given that the future is uncertain and that the optimization decisions influence the time of information discovery for a subset of the uncertain parameters. The standard approach to formulate stochastic programs is based on the assumption that the stochastic process is independent of the optimization decisions, which is not true for the class of problems under consideration. We present a hybrid mixed-integer disjunctive programming formulation for the stochastic program corresponding to this class of problems and hence extend the stochastic programming framework. A set of theoretical properties that lead to reduction in the size of the model is identified. A Lagrangean duality based branch and bound algorithm is also presented. Financial support from the ExxonMobil Upstream Research Company is gratefully acknowledged.     

First Principle Studies to Tailor Graphene Through Synergistic Effect as a Highly Efficient Electrocatalyst for Oxygen Evolution Reaction

The Oxygen Evolution Reaction (OER) is one of the major roadblocks for electrocatalytic oxidation of water (water splitting) and for designing efficient metal-air batteries. Herein, we present a comprehensive study to design graphene based efficient electrocatalyst, modified by doping with main group elements Al, Si, P, S and co-doping with B and N, for OER using DFT computations. Four elementary steps in the OER reaction have been traced, free energy change for each elementary step was calculated considering thermodynamic corrections. Out of all the doped models, S doped graphene shows maximum efficiency that was further enhanced by adjusting the concentration of codopants B and N around the active dopant site. Our results show that synergy between codopants B and N and dopant S atom leads to high electrocatalytic efficiency of modified graphene towards OER and brings down the overpotential to as low as 0.44 V.     

Using diversification,communication and parallelism to solve mixed-integer linear programs

Performance variability of modern mixed-integer programming solvers and possible ways of exploiting this phenomenon present an interesting opportunity in the development of algorithms to solve mixed-integer linear programs (MILPs). We propose a framework using multiple branch-and-bound trees to solve MILPs while allowing them to share information in a parallel execution. We present computational results on instances from MIPLIB 2010 illustrating the benefits of this framework.     

Workforce routing and scheduling for electricity network maintenance with downtime minimization

We investigate a combined routing and scheduling problem for the maintenance of electricity networks. In electricity networks power lines must be regularly maintained to ensure a high quality of service. For safety reasons a power line must be physically disconnected from the network before maintenance work can be performed. After completing maintenance work the power line must be reconnected. Each maintenance job therefore consists of multiple tasks which must be performed at different locations in the network. The goal is to assign each task to a worker and to determine a schedule such that the downtimes of power lines and the travel effort of workers are minimized. For solving this problem, we combine a Large Neighborhood Search meta-heuristic with mathematical programming techniques. The method is evaluated on a large set of test instances which are derived from network data of a German electricity provider.