Synthesis of MoSi2-TiC nanocomposite powder via mechanical alloying and subsequent annealing

MoSi₂-30 wt.% TiC nanocomposite powder was successfully synthesized by ball milling and following heat treatment. Effect of milling time and annealing temperature were investigated. The products synthesis and reactions progress were characterized by XRD. Morphology and microstructure of milled powders were monitored by SEM and TEM, respectively. Results showed that the synthesis of this composite begins after 10 h of milling and progresses gradually up to 30 h of milling. MoSi₂-TiC composite was completely synthesized after annealing of 30 h milled powder at 900 °C. On the basis of Reitveld refinement method, the mean grain size and microstrain of 13.2 nm and 0.44% were obtained, respectively for 30 h milled powder that is in consistent with TEM image. In the spite of grain growth and strain release, this nanocomposite powder maintained its nanostructure after annealing.     

Removal of Silicon Impurity from Molten Brass Using an Innovative ZnO-containing Slag

The elimination kinetics of silicon impurity from molten brass by a novel ZnO-Na₂O-B₂O₃-Na₂CO₃ slag has been studied. The influence of temperature, initial concentrations of Si in molten brass, and initial concentrations of SiO₂ in liquid slag on the kinetics of the reaction was investigated. Experimental results showed that the reaction rate increases with increasing temperature and with decreasing initial concentration of silicon in the metal and silicon dioxide in the slag phase. Based on a kinetic analysis, it was concluded that the reaction is predominantly controlled by mass transfer in the slag phase. The activation energy was estimated to be approximately 197 kJ mol⁻¹.     

Stabilization of gas-lift oil wells by a nonlinear model predictive control scheme based on adaptive neural network models

Producing oil from gas-lift wells are often faced with severe producing oscillatory flow regimes. A major source of the oscillations is recognized as casing–heading instability which is caused by dynamic interaction between injection gas and multiphase fluid. This phenomenon poses strict production-related challenges in terms of lower average production and strain on downstream equipment. In this paper, an effective solution is proposed based on integration of an online interpretation dynamic model and a nonlinear model predictive control (NMPC) scheme. The paper uses adaptive growing and pruning radial basis function (GAP-RBF) neural networks (NNs) to recursively capture the essential dynamics of casing–heading instability in a nonlinear model structure. Extended Kalman filter (EKF) and unscented Kalman filter (UKF) are comparatively investigated to adaptively train modified GAP-RBF NNs. NMPC methodology is developed on the basis of the identified nonlinear NN model for real-time stabilization of casing–heading instability in an oil reservoir equipped with a gas-lift production well. A set of test studies has been conducted to explore the superior performance of the proposed adaptive NMPC controller under different scenarios for an oil reservoir simulated in ECLIPSE and linked to a complementary gas-lifted oil well simulated in programming environment.     

Synthesis of nanocrystalline Bi2Te3 via mechanical alloying

Bi₄₀Te₆₀ thermoelectric compound was fabricated via mechanical milling of bismuth and tellurium as starting materials. Effect of the milling time and heat treatment temperatures were investigated. In order to characterize the ball milled powders, the X-ray diffraction (XRD) was used. Thermal behavior of the mechanically alloyed powders was studied by differential thermal analysis (DTA). The morphological evolutions were studied by scanning electron microscopy (SEM). Results showed that the nanocrystalline Bi₂Te₃ compound was formed after 5 h of milling. Further milling (25 h) and heating to 500 °C showed that the synthesized phase was stable during these conditions. Nanocrystalline Bi₂Te₃ with 9–10 nm mean grain size and flaky morphology (lamellar structure) was obtained at the end of milling.     

Synthetic Biology: A New Tool for the Trade

Protein–protein interactions are fundamental to many biological processes. Yet, the weak and transient noncovalent bonds that characterize most protein–protein interactions found in nature impose limits on many bioengineering experiments. Here, a new class of genetically encodable peptide–protein pairs—isopeptag‐N/pilin‐N, isopeptag/pilin‐C, and SpyTag/SpyCatcher—that interact through autocatalytic intermolecular isopeptide bond formation is described. Reactions between peptide–protein pairs are specific, robust, orthogonal, and able to proceed under most biologically relevant conditions both in vitro and in vivo. As fusion constructs, they provide a handle on molecules of interest, both organic and inorganic, that can be grasped with an iron grip. Such stable interactions provide robust post‐translational control over biological processes and open new opportunities in synthetic biology for engineering programmable and self‐assembling protein nanoarchitectures.     

A comparison of stochastic programming and bi-objective optimisation approaches to robust airline crew scheduling

A prominent problem in airline crew scheduling is the pairings or Tour-of-Duty planning problem. The objective is to determine a set of pairings (or Tours-of-Duty) for a crew group to minimise the planned cost of operating a schedule of flights. However, due to unforeseen events the performance in operation can differ considerably from planning, sometimes causing significant additional recovery costs. In recent years there has been a growing interest in robust crew scheduling. Here, the aim is to find solutions that are “cheap” in terms of planned cost as well as being robust, meaning that they are less likely to be disrupted in case of delays. Taking the stochastic nature of delays into account, Yen and Birge (Transp Sci 40:3–14, 2006) formulate the problem as a two-stage stochastic integer programme and develop an algorithm to solve this problem. Based on the contradictory nature of the goals, Ehrgott and Ryan (J Multi-Criteria Decis Anal 11:139–150, 2002) formulate a bi-objective set partitioning model and employ elastic constraint scalarisation to enable the solution by set partitioning algorithms commercially used in crew scheduling software. In this study, we compare the two solution approaches. We improve the algorithm of Yen and Birge (Transp Sci 40:3–14, 2006) and implement both methods with a commercial crew scheduling software. The results of both methods are compared with respect to characteristics of robust solutions, such as the number of aircraft changes for crew. We also conduct experiments to simulate the performance of the obtained solutions. All experiments are performed using actual schedule data from Air New Zealand.     

Effect of the starting materials on the reaction synthesis of Ti3SiC2

Ternary carbide of titanium and silicon was produced via mechanical milling and following heat treatment. Effects of the starting materials, milling time and heat treatment temperature were studied. X-ray diffraction (XRD) and scanning electron microscopy (SEM) were utilized to evaluate the structural and morphological evolutions of the ball-milled and annealed powders. Results showed that the ball milling of TiO–Si–C as the starting materials failed to synthesize Ti₃SiC₂. Additionally, ball milling the elemental powders for shorter milling times resulted in the activation of the powders. However, after longer milling times, Ti–TiC nanocomposite was obtained. Furthermore, during annealing the milled powders, Ti₃SiC₂–TiC nanocomposite with the mean grain size of 16 nm was synthesized. After 20 h of milling, a very fine microstructure with narrow size of distribution and spheroid particles was achieved.     

Investigating the effect of weather on punctuality of Norwegian railways: a case study of the Nordland Line

The overall punctuality of the railway system is of particular importance for customers in order to use trains as a means of public transport. Investigating the drivers of low punctuality of trains is an essential step for improving their punctuality. Severe weather conditions are assumed to be one of the drivers of delays and low punctuality of the transportation system. This paper addresses the extent to which the weather factors such as temperature, snow, precipitation and wind influence the punctuality of trains on the Norwegian railways. The data for the study are collected from the passenger trains on the Nordland Line. The study period is 10 years, from the beginning of 2007 to the end of 2016. Data are analysed on a daily and weekly basis, and correlation and regression analyses are used to perform the statistical analysis. The results show that extreme cold weather during the winters is a crucial influencing factor contributing to delays and low punctuality. We also found that the weather variable that best explains variations in punctuality of passenger trains on this line is snow depth.

     

Multi-wall carbon nanotubes supported molybdenyl acetylacetonate: Efficient and highly reusable catalysts for epoxidation of alkenes with tert-butyl hydroperoxide

Efficient epoxidation of olefins catalyzed by MoO₂(acac)₂ supported on amines functionalized MWCNTs is reported. The MWCNTs bearing carboxylic acid groups were modified with 2-aminophenol and 2-aminothiophenol. These amine–MWCNTs act as bidentate ligand for attachment of Mo catalyst. These catalysts were characterized by elemental analysis, scanning electron microscopy, FT-IR and diffuse reflectance UV–Vis spectroscopic methods. The prepared catalysts were used for efficient epoxidation of different alkenes such as cyclic and linear ones with tert-butyl hydroperoxide in refluxing 1,2-dichloroethane. These heterogeneous catalysts can be reused several times without significant loss of their catalytic activity.