Fabrication of Functional Nanofibrous Ammonia Sensor

A nanofibrous sensor for ammonia gas is fabricated by electrospinning the composite of poly(diphenylamine) (PDPA) with poly(methyl methacrylate) (PMMA) onto the patterned interdigit electrode. The composite electrospun membrane shows interconnected fibrous morphology. Functional groups in PDPA and the high active surface area of the fibrous membrane make the device detect a lower concentration of ammonia with a good reproducibility. The sensing capability of the device is studied by monitoring the changes in resistance of the membrane with different concentrations of ammonia. The changes in resistance of the membrane shows linearity with the concentration of ammonia in the limit of 10 and 300 ppm. UV-visible spectroscopy reveals the mechanism of sensing ammonia by the membrane.     

Modelling carbon dioxide solubility in ionic liquids

Solubility information for CO₂ in different ionic liquids, ILs, in part can potentially be used to select a specific IL for the separation of CO₂ from hydrocarbon fluids. Unfortunately, not all CO₂–IL systems have been experimentally described at similar temperatures and pressures; therefore, a direct comparison of performance by process simulation is not always possible. In the extreme cases, the design of a CO₂ separation process may require predicting the CO₂–IL equilibria for which there are no available solubility data. To address the need for this information, a semi‐empirical correlation was developed to estimate the dissolution of CO₂ in CO₂–IL solvent systems. The theoretical COSMO–RS calculation method was used to calculate the chemical potential of CO₂ in a wide variety of ILs and the Soave–Redlich–Kwong equation was used to calculate the fugacity coefficient of the CO₂ vapour phase. The model was correlated with available literature data, yielding an average error of AAR = 23% and small bias. © 2012 Canadian Society for Chemical Engineering     

Silver nanoparticles distributed into polyaniline bridged silica network: A functional nanocatalyst having synergistic influence for catalysis

A novel organic–inorganic hybrid nanocatalyst, Ag nanoparticles supported poly[N-(3-Trimethoxy silyl)propyl]aniline (Ag@PTMSPA), was prepared by a simple one-step method. X-ray diffraction analysis, field emission transmission electron microscopy and X-ray photo electron spectroscopy reveal the coexistence of Ag nanoparticles (average size ∼ 10 nm) and PTMSPA in Ag@PTMSPA. N₂ adsorption–desorption experiments provide the textural properties of the catalyst, such as surface area (86.6 m²/g), pore volume (1.3 × 10^− 1 cm³/g) and pore size (4.2 nm). UV–visible spectroscopy was used to follow the kinetics of reduction of 4-nitrophenol (4-NP) by sodium borohydride (NaBH₄) in the presence of Ag@PTMSPA catalyst.     

Experimental flame speed in multi-layered nano-energetic materials

This paper deals with the reaction of dense Metastable Intermolecular Composite (MIC) materials, which have a higher density than conventional energetic materials. The reaction of a multilayer thin film of aluminum and copper oxide has been studied by varying the substrate material and thicknesses. The in-plane speed of propagation of the reaction was experimentally determined using a time of- flight technique. The experiment shows that the reaction is completely quenched for a silicon substrate having an intervening silica layer of less than 200 nm. The speed of reaction seems to be constant at 40 m/s for silica layers with a thickness greater than 1 μm. Different substrate materials such as glass and photoresist were also used.     

Information requirements analysis for holonic manufacturing systems in a virtual environment

The design and development of holonic manufacturing systems requires careful, and sometimes risky, decision making to ensure that they will successfully satisfy the demands of an ever-changing market. In this paper, the authors propose a methodology for a holonic manufacturing systems requirement analysis that is based on a virtual reality approach and aimed at assisting designers of such systems along the entire systems design and development process. Exploiting virtual reality helps the user collect valid information quickly and in a correct form by putting the user and the information support elements in direct relation with the operation of the system in a more realistic environment. A prototype software system tool is designed to realise the features outlined in each phase of the methodology. A virtual manufacturing environment for matching the physical and the information model domains is utilised to delineate the information system requirements of holonic manufacturing systems implementation. A set of rules and a knowledge base is appended to the virtual environment to remove any inconsistency that could arise between the material and the information flows during the requirement analysis.     

Modelling dependable systems using hybrid Bayesian networks

A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems.     

Nitrate Capture Investigation in Plasma-Activated Water and Its Antifungal Effect on Cryptococcus pseudolongus Cells

This research investigated the capture of nitrate by magnesium ions in plasma-activated water (PAW) and its antifungal effect on the cell viability of the newly emerged mushroom pathogen Cryptococcus pseudolongus. Optical emission spectra of the plasma jet exhibited several emission bands attributable to plasma-generated reactive oxygen and nitrogen species. The plasma was injected directly into deionized water (DW) with and without an immersed magnesium block. Plasma treatment of DW produced acidic PAW. However, plasma-activated magnesium water (PA-Mg-W) tended to be neutralized due to the reduction in plasma-generated hydrogen ions by electrons released from the zero-valent magnesium. Optical absorption and Raman spectra confirmed that nitrate ions were the dominant reactive species in the PAW and PA-Mg-W. Nitrate had a concentration-dependent antifungal effect on the tested fungal cells. We observed that the free nitrate content could be controlled to be lower in the PA-Mg-W than in the PAW due to the formation of nitrate salts by the magnesium ions. Although both the PAW and PA-Mg-W had antifungal effects on C. pseudolongus, their effectiveness differed, with cell viability higher in the PA-Mg-W than in the PAW. This study demonstrates that the antifungal effect of PAW could be manipulated using nitrate capture. The wide use of plasma therapy for problematic fungus control is challenging because fungi have rigid cell wall structures in different fungal groups.     

Rotation-invariant fingerprint matching using radon and DCT

A new set of promising rotation-invariant features based on radon and discrete cosine transform (DCT) is proposed for fingerprint matching. The radon and DCT of a tiny area in the region of core point of fingerprint image is computed. In the proposed method only 34% DCT coefficients are used for feature extraction. Competency of this approach is tested on standard databases, namely FVC2002 and FVC2004. This approach provides 70% genuine acceptance rate (GAR) at ~0% false acceptance rate (FAR) and 95% GAR at 10% FAR on rotated and non-rotated databases, respectively. Experimental results prove that the proposed feature extraction approach is rotation invariant.     

Quantitative evaluation of root canal surface roughness after filing with adaptive reciprocating and continuous rotary instruments

Obtaining clean and smooth root canal walls is the ideal clinical outcome of the cleaning and shaping stage in root canal treatment. This study compares the surface roughness of root canal surfaces instrumented with a NiTi filing system with either adaptive reciprocating (AR) or continuous rotation (CR). Root canal cleaning and shaping was carried out on the mesial canals of 24 extracted first molars roots with either AR or CR. Roots were split in half and the surface roughness of their canals was evaluated in 12 three dimensional roughness reconstructions using a scanning electron microscope. Rz (nm) values were calculated in three areas of each reconstruction and analyzed (α = 0.05). Mann‐Whitney tests showed that surface roughness was significantly higher overall in the AR group (Rz = 967 ± 250 nm) compared with the CR group (Rz = 739 ± 239 nm; p = 0.044). The roughness values generally increased from apical towards the coronal third in both groups. A less aggressive finishing file or a continuous rotary system to end the cleaning and shaping stage may be beneficial to reduce roughness of the root canal surface.