Pitting Corrosion Behavior of Cr–Mn Austenitic Stainless Steel with Addition of Molybdate and Tungstate Under Stagnant and Flow Condition in NaCl Solution

Journal of Failure Analysis and Prevention - Molybdate and tungstate inhibitors were introduced in stagnant and flowing conditions for determining pitting corrosion resistance of Cr–Mn SS in...     

Modifying Polyphase Codes to Mitigate Range Side-lobes in Pulse Compression Radar

Wireless Personal Communications - Range side-lobes suppression which is responsible for detection ambiguity is a challenging task in pulse compression (PC) radar. Targets generating weak signals...     

Fault coverage-based test suite optimization method for regression testing: learning from mistakes-based approach

Neural Computing and Applications - This paper presents a novel method referred as fault coverage-based test suite optimization (FCBTSO) for regression test suite optimization. FCBTSO is proposed...     

Defect Engineering in Few‐Layer Phosphorene

Defect engineering in 2D phosphorene samples is becoming an important and powerful technique to alter their properties, enabling new optoelectronic applications, particularly at the infrared wavelength region. Defect engineering in a few‐layer phosphorene sample via introduction of substrate trapping centers is realized. In a three‐layer (3L) phosphorene sample, a strong photoluminescence (PL) emission peak from localized excitons at ≈1430 nm is observed, a much lower energy level than free excitonic emissions. An activation energy of ≈77 meV for the localized excitons is determined in temperature‐dependent PL measurements. The relatively high activation energy supports the strong stability of the localized excitons even at elevated temperature. The quantum efficiency of localized exciton emission in 3L phosphorene is measured to be approximately three times higher than that of free excitons. These results could enable exciting applications in infrared optoelectronics.     

Incremental exemplar learning schemes for classification on embedded devices

Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device’s limited memory resources. Moreover, embedded devices often operate in an environment where data exhibits evolutionary changes which entails frequent update of the in-memory training data. A viable option for dealing with the memory constraint is to use Exemplar Learning (EL) schemes that learn a small memory set (called the exemplar set) of high functional information that fits in memory. However, traditional EL schemes have several drawbacks that make them inapplicable for embedded devices; (1) they have high memory overheads and are unable to handle incremental updates to the exemplar set, (2) they cannot be customized to obtain exemplar sets of any user-defined size that fits in the memory and (3) they learn exemplar sets based on local neighborhood structures that do not offer robust classification performance. In this paper, we propose two novel EL schemes, (Entropy-Based Exemplar Learning) and (AUC-Based Exemplar Learning) that overcome the aforementioned short-comings of traditional EL algorithms. We show that our schemes efficiently incorporate new training datasets while maintaining high quality exemplar sets of any user-defined size. We present a comprehensive experimental analysis showing excellent classification-accuracy versus memory-usage tradeoffs using our proposed methods.     

Hydrogenation behaviour of Ce-based AB5 intermetallic compounds

In the present work, the effect of Zr on the hydrogenation behaviour of CeNi₅ intermetallic compound has been studied. All intermetallic compounds have been synthesized by arc melting method in the argon atmosphere and well characterized by the means of XRD and SEM. The elemental composition of each sample has also been investigated using EDX technique. EDX spectrum confirms the elements present in the sample and the exact quantitative composition of these elements. The lattice constant and volume was found to increase with Zr substitution. Pressure composition isotherm has been carried out for CeNi_5−xZr_x (x = 1, 2) alloys in the temperature and pressure ranges of 293 ≤ T ≤ 333 K and 0.5 ≤ P ≤ 35 bar, respectively. The plateau pressure was found to reduce significantly, which makes these alloys more useful for practical applications in comparison to parent alloy (CeNi₅). The enthalpy and entropy for the systems has been calculated using Van’t Hoff plot.     

Transient solute adsorption incorporated modeling and simulation of unstirred dead-end ultrafiltration of macromolecules: An approach based on self-consistent field theory

An unsteady state mass transfer model of unstirred dead-end ultrafiltration module has been developed in the present study. The dynamic membrane surface concentration is evaluated using a modified self-consistent field theory, which enables the development of an algorithm to incorporate the contribution of solute adsorption in the membrane surface concentration dynamics. Knowing the corrected membrane surface concentration, permeate flux and permeate side concentration is determined using osmotic pressure model and flux–rejection relation as predicted by irreversible thermodynamics. The time evolution of all the different process variables is achieved by solving two component balance equations developed at the membrane surface and in the solution phase respectively. The basic feature of the model is the incorporation of adsorbed fraction in the unsteady state membrane surface concentration. For the validation of the proposed model, experiments were conducted with Bovine Serum Albumin (BSA)/water as feed in a standard unstirred batch ultrafiltration module fitted with Polyethersulfone (PES) membrane of 30 kDa molecular weight cut-off (MWCO). The model predicted flux and the permeate concentration were found to be in good agreement with the experimental data.     

Synthesis,characterization and thermal degradation of dual temperature‐ and pH‐sensitive RAFT‐made copolymers of N,N‐(dimethylamino)ethyl methacrylate and methyl methacrylate

Poly{[(N,N‐(dimethylamino)ethyl methacrylate]‐co‐(methyl methacrylate)} copolymers of various compositions were synthesized by reversible addition‐fragmentation chain transfer (RAFT) polymerization at 70 °C in N,N‐dimethylformamide. The polymer molecular weights and molecular weight distributions were obtained from size exclusion chromatography, and they indicated the controlled nature of the RAFT polymerizations; the polydispersity indices are in the range 1.1–1.3. The reactivity ratios of N,N‐(dimethylamino)ethyl methacrylate (DMAEMA) and methyl methacrylate (MMA) (r_DMAEMA = 0.925 and r_MMA = 0.854) were computed by the extended Kelen–Tüdös method at high conversions, using compositions obtained from ¹H NMR. The pH‐ and temperature‐sensitive behaviour were studied in aqueous solution to confirm dual responsiveness of these copolymers. The thermal properties of the copolymers with various compositions were investigated by differential scanning calorimetry and thermogravimetric analysis. The kinetics of thermal degradation were determined by Friedmann and Chang techniques to evaluate various parameters such as the activation energy, the order and the frequency factor. © 2012 Society of Chemical Industry