Hot corrosion behavior of plasma and HVOF sprayed Co- and Ni-based coatings at 900°C

High temperature Co- and Ni-based metallic coatings were applied on samples of 310 stainless steel using plasma spray and high velocity oxy fuel (HVOF) methods. The samples were sprayed with Na₂SO₄, V₂O₅ and NaCl salt solutions and exposed in air at 900°C to cyclic conditions with an aim to simulate an environment typically encountered in oil refinery operation. Extent of hot corrosion damage was assessed using gravimetric measurements while microstructure of the coatings was examined using scanning electron microscopy coupled with energy dispersive X-ray spectroscopy. X-ray diffraction was used to determine phase constitution. The aim of this study was to evaluate and compare the performance of specific coatings in hot corrosive environments. Experimental results indicate that the presence of V₂O₅ and NaCl serves to enhance hot corrosion while Co-based coatings perform better than Ni-based coating.     

Formulation and Evaluation of an Automatic Dishwashing Detergent Containing T1 Lipase

The use of enzymes in detergent formulations is becoming popular due to the concerns about the environment. T1 lipase (E.C. 3.1.1.3) was evaluated for its stability and performance in dishwashing along with other common components of an automatic dishwashing detergent. Therefore, the process of formulating the detergent would depend on the stability of T1 lipase, which may also reflect the performance during the washing. T1 lipase was mostly stable in nonionic surfactants, especially those that were made of polyhydric alcohols. T1 lipase was also stable in a mixture of sodium carbonate and glycine. However, sodium carbonate alone destabilized T1 lipase possibly due to the interaction between carbonates and Ca²⁺. These results indicated that polyhydric alcohols and glycine had stabilizing effects on T1 lipase. The dishwashing performance was evaluated in term of percent soil removed. The dishwashing performance of the formulated detergent was positively affected by the increase in temperature but negatively affected by the presence of hard water, specifically Ca²⁺ and Mg²⁺. However, T1 lipase was not negatively affected by the presence of hard water, and this enzyme was enhanced by the presence of polyacrylates. The presence of Ca²⁺ improved the structural integrity of T1 lipase. It is generally known that most enzymes that depend on Ca²⁺ for their structural integrity would be greatly destabilized in the presence of metal chelators; thus, stabilizing strategies such as adding glycine would be essential to maintain enzyme activity during the wash.     

Easily made and handled carbon nanocones for scanning tunneling microscopy and electroanalysis

Well-formed carbon nanocones at the ends of micrometer-diameter carbon fibers (CFs) were fashioned into functional tips for scanning tunneling microscopy (STM) and miniaturized voltammetric sensors. Sharpening of single graphite filaments was achieved by simple DC electrochemical etching in 0.1 N NaOH. Operated as STM tips, pointed CFs resolved in air the contour and surface morphology of a nanoscopic Au line pattern and imaged in vacuum a Si (1 1 1) surface with clear atomic resolution. Subjecting already etched CFs to tip-sparing insulation with electrodeposited paint produced conical carbon ultramicroelectrodes (UMEs) with effective radii down to about 900 nm. Comparative cyclic voltammetry trials in alkaline, neutral and acidic solutions showed that the conical carbon UME’s had a wider practical potential window for electroanalytic applications than, for instance, Pt disk UMEs. The CF-based conical sensors described here are exceptionally easy to make with simple laboratory equipment and perform well in STM topography imaging and voltammetry. The inherent simplicity of sensor production widens the field of potential users, and offers clear advantages over existing types of UMEs, in particular those based on carbon nanotubes, which are especially hard to handle in an optical microscope setting.     

Optimisation study of large‐scale enzymatic synthesis of oleyl oleate,a liquid wax ester,by response surface methodology

An optimisation study of the large‐scale enzymatic synthesis of a liquid wax ester from oleic acid and oleyl alcohol using Novozym 435 was carried out. Investigations were performed in batch mode with a stirred tank reactor (STR) with one multi‐bladed impeller. Response surface methodology (RSM) based on a five‐level, three‐variable central composite rotatable design (CCRD) was used to evaluate the interactive effects of various parameters. The parameters are amount of enzyme (A) (90–120 g), impeller speed (B) (100–400 rpm) and temperature (C) (40–60 °C). The optimum conditions derived via RSM at a fixed reaction time of 1 h were successfully optimised as A = 104 g, B = 388.0 rpm and C = 49.7 °C. The actual experimental yield was 96.7% under the optimum conditions, which compared well with the maximum predicted value of 97.6%. Copyright © 2005 Society of Chemical Industry     

Investigating Factors Affecting Water-In-Diesel Fuel Nanoemulsions

In this work, water-in-diesel fuel nanoemulsions were prepared with mixed nonionic surfactants. Several mixtures of sorbitan monooleate and polyoxyethylene (20) sorbitan monooleate, with different Hydrophilic–Lipophilic Balance (HLB) values (9.6, 9.8, 10, 10.2 and 10.4) were prepared to achieve the optimal HLB value. Three mixed surfactant concentrations were prepared at 6, 8 and 10 wt% to identify the optimum concentration. Five emulsions with different water contents: 5, 6, 7, 8 and 9 % (wt/wt) were prepared using a high energy method under the optimum conditions (HLB = 10 and mixed surfactant concentration = 10 %). The effect of the HLB value, mixed surfactant concentration and water content on the droplet size has been studied. The interfacial tension and thermodynamic properties of the individual and the blended emulsifiers were investigated. Droplet size of the prepared nanoemulsions was determined by dynamic light scattering and the nanoemulsion stability was assessed by measuring the variation of the droplet size as a function of time. From the results obtained, it was found that the mean droplet size was formed between 49.5 and 190 nm depending on the HLB value, surfactant concentration and water content of the blended emulsifiers.     

Network-level accident-mapping: Distance based pattern matching using artificial neural network

The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily ‘transferable’ as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in “learning” the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that the accuracy is much better than other methods.     

Magnetic Properties of Mechanically Alloyed Cobalt-Zinc Ferrite Nanoparticles

In this work, the physical and the magnetic properties of cobalt-zinc ferrite nanoparticles, synthesized via high-energy ball milling (HEBM), were examined. X-Ray diffraction (XRD), field emission scanning electron microscopy (FeSEM), and scanning transmission electron microscopy (STEM) were used to study changes of the powder structure and morphology analyses. Hysteresis and permeability measurement were carried out using a BH hysteresisgraph system and an impedance analyzer, respectively. The results suggested improved magnetic properties of Co_0.5Zn_0.5Fe₂O₄ with increasing sintering temperature from 950 °C up to 1200 °C. However, the variations of the magnetic responses were consistent with the varying volume concentration of the ferrite composites. Unlike the highly crystalline pure ferrite which showed magnetic resonance within the measured frequency, the crystallineamorphous composites showed no visible resonance peak. This proved that the resonance peak shifted to higher frequency as a result of the single domain spin behavior in the absence of domain walls movement.     

Simultaneous photoreductive removal of copper (II) and selenium (IV) under visible light over spherical binary oxide photocatalyst

Waste water of copper mines and copper processing plant contains both copper and selenium ions with other contaminants. In this paper simultaneous photoreductive removal of copper (II) and selenium (IV) is studied for the first time using spherical binary oxide photocatalysts under visible light. All the synthesized materials are found to be mesoporous in nature with reasonably high surface area. Among a range of hole scavengers, only EDTA (ethylene diamine tetraacetic acid) and formic acid are found to be the most active for the reduction reaction. A comparative study is carried out using both the hole scavengers varying reaction time, concentration, pH etc. For a single contaminant, EDTA is found to be the best for Cu(II) reduction whereas formic acid is the best for Se(IV) reduction. In a mixed solution both EDTA and formic acid perform very well under visible light irradiation. Highest photocatalytic reduction in a mixed solution is observed at pH 3. Among all the synthesized materials, TiZr-10 performs as the best photocatalyst for both Cu(II) and Se(IV) reduction. However under UV light, Degussa P25 performs slightly better than TiZr-10. Present study shows that 100 ppm of mixed solution can be removed under visible light in 40 min of reaction using TiZr-10 as catalyst. Photodeposited material is found to be copper selenide rather than pure copper and selenium metal. This indicates that the waste water containing copper and selenium ions can be efficiently treated under visible or solar light.