A PVC plasticized membrane sensor for nickel ions

A new PVC membrane sensor, which is highly selective towards Ni (II) ions, has been developed using a thiophene-derivative Schiff base as the ionophore. The best performance was exhibited by the membrane having the composition percentage ratio of 5:3:61:31 (ionophore:NaTPB:DBP:PVC) (w=w), where NaTPB is the anion excluder, sodium tetraphenylborate and DBP is the plasticizing agent (dibutyl phthalate). The membrane exhibited a good Nernstian response for nickel ions over the concentration range of 1.0 10 1– 5.0 10 6M (limit of detection is 1.8 10 6 M) with a slope of 29.5 1.0mV per decade of activity. It has a fast response time of<20 s and can be used for a period of 4 months with good reproducibility. The sensor is suitable for use in aqueous solutions of a wide pH range of 3.2–7.9. The sensor shows high selectivity to nickel ions over a large number of mono-, bi- and trivalent cations. It has been successfully used as an indicator electrode in the potentiometric titration of nickel ions against EDTA and also for direct determination of nickel content in real samples – wastewater samples from electroplating industries and Indian chocolates.

A PVC Plasticized Membrane Sensor for Nickel Ions

A new PVC membrane sensor, which is highly selective towards Ni (II) ions, has been developed using a thiophene-derivative Schiff base as the ionophore. The best performance was exhibited by the membrane having the composition percentage ratio of 5:3:61:31 (ionophore:NaTPB:DBP:PVC) (w=w), where NaTPB is the anion excluder, sodium tetraphenylborate and DBP is the plasticizing agent (dibutyl phthalate). The membrane exhibited a good Nernstian response for nickel ions over the concentration range of 1.0 10 1– 5.0 10 6M (limit of detection is 1.8 10 6 M) with a slope of 29.5 1.0mV per decade of activity. It has a fast response time of<20 s and can be used for a period of 4 months with good reproducibility. The sensor is suitable for use in aqueous solutions of a wide pH range of 3.2–7.9. The sensor shows high selectivity to nickel ions over a large number of mono-, bi- and trivalent cations. It has been successfully used as an indicator electrode in the potentiometric titration of nickel ions against EDTA and also for direct determination of nickel content in real samples – wastewater samples from electroplating industries and Indian chocolates.

A PVC Plasticized Sensor for Ni(II) Ion Based on a Simple Ethylenediamine Derivative

new PVC membrane ion selective electrode which is highly selective towards Ni(II) ions was constructed using a Schiff base containing a binaphthyl moiety as the ionophore. The sensor exhibited a good Nernstian response for nickel ions over the concentration range 1.0 × 10–1 – 5.0 × 10–6 M with a lower limit of detection of 1.3 × 10–6 M. It has a fast response time and can be used for a period of 4 months with a good reproducibility. The sensor is suitable for use in aqueous solutions in a wide pH range of 3.6 – 7.4 and works satisfactorily in the presence of 25% (v/v) methanol or ethanol. The sensor shows high selectivity to nickel ions over a wide variety of cations. It has been successfully used as an indicator electrode in the potentiometric titration of nickel ions against EDTA and also for the direct determination of nickel content in real samples: effluent samples, chocolates and hydrogenated oils.

Growth and Characterisation of Radio Frequency Magnetron Sputttered Indium Tin Oxide Thin Films

The increasing interest in the interaction of light with electricity and electronically active materials made the materials and techniques for producing semitransparent electrically conducting films particularly attractive. Transparent conductors have found major applications in a number of electronic and optoelectronic devices including resistors, transparent heating elements, antistatic and electromagnetic shield coatings, transparent electrode for solar cells, antireflection coatings, heat reflecting mirrors in glass windows and many other. Tin doped indium oxide (indium tin oxide or ITO) is one of the most commonly used transparent conducting oxides. At present and likely well into the future this material offers best available performance in terms of conductivity and transmittivity combined with excellent environmental stability, reproducibility and good surface morphology. Although partial transparency, with a reduction in conductivity, can be obtained for very thin metallic films, high transparency and simultaneously high conductivity cannot be attained in intrinsic stoichiometric materials. The only way this can be achieved is by creating electron degeneracy in a wide bandgap (Eg > 3eV or more for visible radiation) material by controllably introducing non-stoichiometry and/or appropriate dopants. These conditions can be conveniently met for ITO as well as a number of other materials like Zinc oxide, Cadmium oxide etc. ITO shows interesting and technologically important combination of properties viz high luminous transmittance, high IR reflectance, good electrical conductivity, excellent substrate adherence and chemical inertness. ITO is a key part of solar cells, window coatings, energy efficient buildings, and flat panel displays. In solar cells, ITO can be the transparent, conducting top layer that lets light into the cell to shine the junction and lets electricity flow out. Improving the ITO layer can help improve the solar cell efficiency. A transparent ii conducting oxide is a material with high transparency in a derived part of the spectrum and high electrical conductivity. Beyond these key properties of transparent conducting oxides (TCOs), ITO has a number of other key characteristics. The structure of ITO can be amorphous, crystalline, or mixed, depending on the deposition temperature and atmosphere. The electro-optical properties are a function of the crystallinity of the material. In general, ITO deposited at room temperature is amorphous, and ITO deposited at higher temperatures is crystalline. Depositing at high temperatures is more expensive than at room temperature, and this method may not be compatible with the underlying devices. The main objective of this thesis work is to optimise the growth conditions of Indium tin oxide thin films at low processing temperatures. The films are prepared by radio frequency magnetron sputtering under various deposition conditions. The films are also deposited on to flexible substrates by employing bias sputtering technique. The films thus grown were characterised using different tools. A powder x-ray diffractometer was used to analyse the crystalline nature of the films. The energy dispersive x-ray analysis (EDX) and scanning electron microscopy (SEM) were used for evaluating the composition and morphology of the films. Optical properties were investigated using the UVVIS- NIR spectrophotometer by recording the transmission/absorption spectra. The electrical properties were studied using vander Pauw four probe technique. The plasma generated during the sputtering of the ITO target was analysed using Langmuir probe and optical emission spectral studies.

ANALYSIS, MODIFICATION, AND EVALUATION OF THE COLD FLOW PROPERTIES OF VEGETABLE OILS AS BASE OIL FOR INDUSTRIAL LUBRICANTS

Poor cold flow properties of vegetable oils are a major problem preventing the usage of many abundantly available vegetable oils as base stocks for industrial lubricants. The major objective of this research is to improve the cold flow properties of vegetable oils by various techniques like additive addition and different chemical modification processes. Conventional procedure for determining pour point is ASTM D97 method. ASTM D97 method is time consuming and reproducibility of pour point temperatures is poor between laboratories. Differential Scanning Calorimetry (DSC) is a fast, accurate and reproducible method to analyze the thermal activities during cooling/heating of oil. In this work coconut oil has been chosen as representative vegetable oil for the analysis and improvement cold flow properties since it is abundantly available in the tropics and has a very high pour point of 24 °C. DSC is used for the analysis of unmodified and modified vegetable oil. The modified oils (with acceptable pour points) were then subjected to different tests for the valuation of important lubricant properties such as viscometric, tribological (friction and wear properties), oxidative and corrosion properties.A commercial polymethacrylate based PPD was added in different percentages and the pour points were determined in each case. Styrenated phenol(SP) was added in different concentration to coconut oil and each solution was subjected to ASTM D97 test and analysis by DSC. Refined coconut oil and other oils like castor oil, sunflower oil and keranja oil were mixed in different proportions and interesterification procedure was carried out. Interesterification of coconut oil with other vegetable oils was not found to be effective in lowering the pour point of coconut oil as the reduction attained was only to the extent of 2 to 3 °C.Chemical modification by acid catalysed condensation reaction with coconut oil castor oil mixture resulted in significant reduction of pour point (from 24 ºC to -3 ºC). Instead of using triacylglycerols, when their fatty acid derivatives (lauric acid- the major fatty acid content of coconut oil and oleic acid- the major fatty acid constituents of monoand poly- unsaturated vegetable oils like olive oil, sunflower oil etc.) were used for the synthesis , the pour point could be brought down to -42 ºC. FTIR and NMR spectroscopy confirmed the ester structure of the product which is fundamental to the biodegradability of vegetable oils. The tribological performance of the synthesised product with a suitable AW/EP additive was comparable to the commercial SAE20W30 oil. The viscometric properties (viscosity and viscosity index) were also (with out additives) comparable to commercial lubricants. The TGA experiment confirmed the better oxidative performance of the product compared to vegetable oils. The sample passed corrosion test as per ASTM D130 method.

Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

Wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions