Maghnite‐H+, a solid catalyst for the cationic polymerization of α‐methylstyrene

The polymerization of α‐methylstyrene (AMS) catalyzed by Maghnite‐H⁺ (Mag‐H) was investigated. Mag‐H is a montmorillonite sheet silicate clay, exchanged with protons. It was found that the cationic polymerization of AMS is initiated by Mag‐H at ambient temperature in bulk and in solution. The effect of the amount of Mag‐H, the temperature, and the solvent was studied. The polymerization rate increased with increase in the temperature and the proportion of catalyst, and it was larger in nonpolar solvents. These results indicated the cationic nature of the polymerization. It may be suggested that the polymerization is initiated by proton addition to monomer from Mag‐H. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Scaling study of cavitation pitting from cavitating jets and ultrasonic horns

Cavitation erosion prediction and characterization of cavitation field strength are of interest to industries suffering from cavitation erosion detrimental effects. One means to evaluate cavitation fields and materials is to examine pitting rates during the incubation period, where the test sample undergoes localized permanent deformations shaped as individual pits. In this study, samples from three metallic materials, an Aluminum alloy (Al 7075), a Nickel Aluminum Bronze (NAB) and a Duplex Stainless Steel (SS A2205) were subjected to a vast range of cavitation intensities generated by cavitating jets at different driving pressures and by an ultrasonic horn. The resulting pitted sample surfaces were examined and characterized with a non-contact 3D optical scanner and the resulting damage computer-analyzed. A statistical analysis of the pit population and its characteristics was then carried out. It was found that the various cavitation field strengths can be correlated to the measured pit distributions and that two characteristic quantities: a characteristic number of pits per unit surface area and unit time, and a characteristic pit diameter or a characteristic pit depth can be attributed to a given “cavitation intensity level”. This characterization concept can be used in the future to study the cavitation intensity of the full scale and to develop methods of full scale predictions based on model scale erosion data.     

Material and velocity effects on cavitation erosion pitting

Cavitation erosion during the incubation period was investigated via pitting tests conducted on three different materials: an Aluminum alloy, a Nickel Aluminum Bronze alloy and a Duplex Stainless Steel. Pitting tests were conducted in a cavitation tunnel in the velocity range 45–90 m/s at a constant cavitation number. The test section was made of a straight nozzle 16 mm in diameter discharged into the radial 2.5 mm space between two flat walls. Cavitation appears in the form of a toroidal cavity attached to the nozzle exit and damage on the samples facing the nozzle is concentrated in a circular ring centered in the cavity closure region. The exposure time was adjusted to avoid pit overlapping. The material surface was examined using a conventional contact profilometer which allowed us to identify the pits, count them, and measure their main characteristics such as depth, surface area, and volume. From these the pitting rate, the coverage rate, and the depth of deformation rate were defined. Pits were classified according to their diameter. For all materials and operating conditions, pitting rate appears to follow an exponential law in relation to the pit diameter. This law depends upon two parameters only, which were identified as the coverage time τ (i.e. the time required for the surface to be covered by erosion pits) and a characteristic pit diameter δ, which corresponds to the pits whose contribution to the coverage process is the highest. Scaling laws for pitting were derived accounting for both material properties and flow velocity, and a procedure to make pitting test results non-dimensional is proposed. The influence of the material on pitting test results was analyzed. It is shown that the damage is not correlated in simple terms with the elastic limit determined from conventional tensile tests and it is conjectured that other parameters such as the strain rate might play a significant role and should be included in the analysis. The effect of flow velocity on both parameters τ and δ was analyzed and a classical power law was found for the influence of the flow velocity on pitting rate for all three materials. Finally, some analysis and discussion is given concerning distributions of pit volume and pit depth.     

Computer modelling and analysis of the photodegradation effect in a-Si:H p-i-n solar cell

Using a previous model, which was developed to describe the light-induced creation of the defect density in the a-Si:H gap states, we present in this work a numerical modelling of the photodegradation effect in the a-Si:H p-i-n solar cell under continuous illumination. We first considered the simple case of a monochromatic light beam with a wavelength λ between 530-540 nm non uniformly absorbed, then the global standard solar spectrum (AM 1.5) illumination is taken into account. The photodegradation is analysed on the basis of the resulting changes in the free carrier's densities, recombination rate, band structure, electrical potential and field, space charge, and current densities. Changes in the cell's external parameters: the open circuit voltage V_oc, the short circuit current density J_sc, the fill factor FF and the maximum power density P_max are also presented.     

A MODIFIED DECOMPOSITION ALGORITHM FOR SCHEDULING PROBLEMS

A decomposition approach developed by the author is modified to reduce the computational effort involved. The modified algorithm is discussed. Computational experiments have been conducted for comparative evaluation of both original and modified decomposition algorithms. Significant results are reported.     

Automatic model selection for the optimization of SVM kernels

This approach aims to optimize the kernel parameters and to efficiently reduce the number of support vectors, so that the generalization error can be reduced drastically. The proposed methodology suggests the use of a new model selection criterion based on the estimation of the probability of error of the SVM classifier. For comparison, we considered two more model selection criteria: GACV (‘Generalized Approximate Cross-Validation’) and VC (‘Vapnik-Chernovenkis’) dimension. These criteria are algebraic estimates of upper bounds of the expected error. For the former, we also propose a new minimization scheme. The experiments conducted on a bi-class problem show that we can adequately choose the SVM hyper-parameters using the empirical error criterion. Moreover, it turns out that the criterion produces a less complex model with fewer support vectors. For multi-class data, the optimization strategy is adapted to the one-against-one data partitioning. The approach is then evaluated on images of handwritten digits from the USPS database.     

A recursive algorithm for solving “a secret sharing” problem

Abstract

This paper presents a recursive algorithm for solving “a secret sharing” problem. This problem is one of the unsolved problems in the Second International Students Olympiad in Cryptography (NSUCRYPTO2015). Recently, Geut et al. solved the problem in a special case. We show that our algorithm is able to solve it in general.     

Life cycle optimization of building energy systems

A life cycle optimization model intended to potentially reduce the environmental impacts of energy use in commercial buildings is presented. A combination of energy simulation, life cycle assessment, and operations research techniques are used to develop the model. In addition to conventional energy systems, such as the electric grid and a gas boiler, cogeneration systems which concurrently generate power and heat are investigated as an alternative source of energy. Cogeneration systems appeared to be an attractive alternative to conventional systems when considering life cycle environmental criteria. Internal combustion engine and microturbine (MT) cogeneration systems resulted in a reduction of up to 38% in global warming potential compared with conventional systems, while solid oxide fuel cell and MT cogeneration systems resulted in a reduction of up to 94% in tropospheric ozone precursor potential (TOPP). Results include a Pareto-optimal frontier between reducing costs and reducing the selected environmental indicators.     

Formation of nanostructured silicon surfaces by stain etching

In this work, we report the fabrication of ordered silicon structures by chemical etching of silicon in vanadium oxide (V₂O₅)/hydrofluoric acid (HF) solution. The effects of the different etching parameters including the solution concentration, temperature, and the presence of metal catalyst film deposition (Pd) on the morphologies and reflective properties of the etched Si surfaces were studied. Scanning electron microscopy (SEM) was carried out to explore the morphologies of the etched surfaces with and without the presence of catalyst. In this case, the attack on the surfaces with a palladium deposit begins by creating uniform circular pores on silicon in which we distinguish the formation of pyramidal structures of silicon. Fourier transform infrared spectroscopy (FTIR) demonstrates that the surfaces are H-terminated. A UV-Vis-NIR spectrophotometer was used to study the reflectance of the structures obtained. A reflectance of 2.21% from the etched Si surfaces in the wavelength range of 400 to 1,000 nm was obtained after 120 min of etching while it is of 4.33% from the Pd/Si surfaces etched for 15 min.