The synthesis and characterization of Cu(II) phthalocyanine bearing peripheral monoazacrown ethers and a spectral investigation of its film forming character

The synthesis, liquid crystalline behavior and self-organizing properties of Cu(II)Pc bearing monoazacrown ether moieties that contain long alkyloxyphenyl N-pivotal groups are described. The Cu(II) phthalocyanine derivative has a hexagonal, columnar structure; optical absorption and vibrational spectroscopy revealed a predominantly co-facial interaction between the chromophores and their orientation parallel to a NaCl surface. It is proposed that such homeotropic alignment is attributable to the ability of the pendant monoazacrown ether groups to coordinate the Na⁺ ions within the NaCl surface.     

Magnetotransport study on as-grown and annealed n- and p-type modulation-doped GaInNAs/GaAs strained quantum well structures

We report the observation of thermal annealing- and nitrogen-induced effects on electronic transport properties of as-grown and annealed n- and p-type modulation-doped Ga_{1 - x}In_xN_yAs_{1 - y} (x = 0.32, y = 0, 0.009, and 0.012) strained quantum well (QW) structures using magnetotransport measurements. Strong and well-resolved Shubnikov de Haas (SdH) oscillations are observed at magnetic fields as low as 3 T and persist to temperatures as high as 20 K, which are used to determine effective mass, 2D carrier density, and Fermi energy. The analysis of temperature dependence of SdH oscillations revealed that the electron mass enhances with increasing nitrogen content. Furthermore, even the current theory of dilute nitrides does not predict a change in hole effective mass; nitrogen dependency of hole effective mass is found and attributed to both strain- and confinement-induced effects on the valence band. Both electron and hole effective masses are changed after thermal annealing process. Although all samples were doped with the same density, the presence of nitrogen in n-type material gives rise to an enhancement in the 2D electron density compared to the 2D hole density as a result of enhanced effective mass due to the effect of nitrogen on conduction band. Our results reveal that effective mass and 2D carrier density can be tailored by nitrogen composition and thermal annealing-induced effects.

PACS

72.00.00; 72.15.Gd; 72.80.Ey     

Synthesis and characterization of novel fluorine‐containing methacrylate copolymers: Reactivity ratios,thermal properties,and antimicrobial activity

The free‐radical‐initiated copolymerization of 2‐(4‐acetylphenoxy)‐2‐oxoethyl‐2‐methylacrylate (AOEMA) and 2‐(4‐benzoylphenoxy)‐2‐oxoethyl‐2‐methylacrylate (BOEMA) with 2‐[(4‐fluorophenyoxy]‐2‐oxoethyl‐2‐methylacrylate (FPEMA) were carried out in 1,4‐dioxane solution at 65°C using 2,2′‐azobisisobutyronitrile as an initiator with different monomer‐to‐monomer ratios in the feed. The monomers and copolymers were characterized by FTIR and ¹H‐ and ¹³C‐NMR spectral studies. ¹H‐NMR analysis was used to determine the molar fractions of AOEMA, BOEMA, and FPEMA in the copolymers. The reactivity ratios of the monomers were determined by the application of Fineman‐Ross and Kelen‐Tudos methods. The analysis of reactivity ratios revealed that BOEMA and AOEMA are less reactive than FPEMA, and copolymers formed are statistically in nature. The molecular weights (M _w and M _n) and polydispersity index of the polymers were determined using gel permeation chromatography. Thermogravimetric analysis of the polymers reveals that the thermal stability of the copolymers increases with an increase in the mole fraction of FPEMA in the copolymers. Glass transition temperatures of the copolymers were found to decrease with an increase in the mole fraction of FPEMA in the copolymers. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Solution-processed LiF for work function tuning in electrode bilayers

Although ambient processing is the key to low-cost organic solar cell production, high-vacuum thermal evaporation of LiF is often a limiting step, motivating the exploration of solution processing of LiF as an alternative electrode interlayer. Submonolayer films are realized with the assistance of polymeric micelle reactors that enable LiF particle deposition with controlled nanoscale surface coverage. Scanning Kelvin probe reveals a work function tunable with nanoparticle coverage with higher values than that of bare indium tin oxide (ITO).     

Enzyme‐assisted aqueous extraction of safflower oil: optimisation by response surface methodology

Aqueous enzymatic oil extraction of safflower seeds was assisted by Alcalase 2.5L and Celluclast 1.5L. Enzyme type and amount, pH, time, temperature, churning rate, dilution ratios and particle size were varied to determine their influence on the oil amount. The amount of oil recovered was higher using seeds ground to a particle size of <0.6 mm. Response surface methodology was employed for the optimisation of aqueous enzymatic oil extraction conducted with Celluclast 1.5L. When the extraction was assisted by Celluclast 1.5L, the maximum oil amount and yield were 33.3 (% w/w) and 79.7 (% w/w), respectively. The optimum conditions were 48.3 °C; 0.25 mL enzyme g^?1 substance; pH, 4.84; resulting oil amount and yield were 28.2 (% w/w) 65 (% w/w), respectively. The predicted critical values were experimentally verified, and an oil amount of 27.1 (% w/w) was achieved. The enzyme treatment did not have any determining effect on the physicochemical properties of extracted oil.     

An expert system for determining candidate software classes for refactoring

In the lifetime of a software product, development costs are only the tip of the iceberg. Nearly 90% of the cost is maintenance due to error correction, adaptation and mainly enhancements. As Lehman and Belady [Lehman, M. M., & Belady, L. A. (1985). Program evolution: Processes of software change. Academic Press Professional.] state that software will become increasingly unstructured as it is changed. One way to overcome this problem is refactoring. Refactoring is an approach which reduces the software complexity by incrementally improving internal software quality. Our motivation in this research is to detect the classes that need to be rafactored by analyzing the code complexity. We propose a machine learning based model to predict classes to be refactored. We use Weighted Naïve Bayes with InfoGain heuristic as the learner and we conducted experiments with metric data that we collected from the largest GSM operator in Turkey. Our results showed that we can predict 82% of the classes that need refactoring with 13% of manual inspection effort on the average.     

A novel Central Composite Design based response surface methodology optimization study for the synthesis of Pd/CNT direct formic acid fuel cell anode catalyst

At present, carbon nanotube supported Pd catalysts are synthesized via NaBH₄ reduction method to investigate their electro catalytic activity thorough formic acid electro oxidation. In order to optimize the synthesis conditions such as %Pd amount (X₁), NaBH₄ amount (times, X₂), water amount (ml, X₃), and time (min., X₄), Central Composite Design (CCD) experiments are designed and determined by the Design-Expert program to determine the maximum observed current (mA/mgPd). Formic acid electro oxidation current density of the catalyst is computed by the model as 974.80 mA/mg Pd for the catalyst prepared at optimum operating conditions (41.14 for %Pd amount, 280.23 NaBH₄ amount, 26.80 ml water amount, and 167.14 min time) obtained with numerical optimization method in CCD. This computed value is very close to the experimentally measured value as 920 mA/mg Pd. Finally, formic acid fuel cell measurements were performed on the Pd/CNT catalyst prepared at optimum operating conditions and compared with the commercial Pd black and Pt black catalysts. As a result, Pd/CNT exhibits better performance compared to Pd black, revealing that Pd/CNT is a promising catalyst for the direct formic acid fuel cell measurements.     

A physics-based, analytical heterojunction bipolar transistormodel, including thermal and high-current effects

A detailed, analytical model for predicting the DC and high-frequency performance of AlGaAs/GaAs graded heterojunction bipolar transistors (HBTs) is presented. The model is developed based on the relevant device physics, such as current-induced base pushout and thermal effects. The current gain, cutoff frequency, and maximum frequency versus the collector current density, which is a function of the applied voltage as well as the corresponding temperature in the HBT, are calculated. The results suggest that the conventional HBT model, which assumes the HBT temperature is the same as that of the ambient, can overestimate the three figures of merit considerably when the collector current density is high. Furthermore, it is shown that the present model correctly explains such experimentally observed HBT high-current behavior as the rapid falloff of the current gain and cutoff frequency. The model predictions compare favorably with the results obtained from a model which solves numerically the Poisson and continuity equations coupled with the lattice heat equation