In this paper, a rapid and sensitive modified electrode for the determination of hydroquinone (HQ) is proposed. In this study, active compound HQ was determined from commercial drug form based on electrochemical oxidation properties at various electrodes by voltammetric methods. Electrodes modified by the electrodeposition of conducting organic polymers such as poly(3-methylthiophene, PMT), polypyrrole (PPY) and polyaniline (PAN) were used as chemical sensors for voltammetric analysis and flow injection detection of HQ. The electrochemical behavior of HQ at conducting polymer electrodes was compared and the effects on behavior of electrolyte type and its pH and the film thickness were systematically examined. The results showed that the proposed modified surface catalyzes the oxidation of HQ. Electrocatalytic efficiency decreases in order of PMT > PPY > PAN. Voltammetric peak positions were affected by the nature of the electrolyte and its pH. Also, the effect of increasing film thickness was to observe increased peak heights for oxidation potential of HQ. The best results for the determination of HQ were obtained by DPV in Na2SO4 (pH 2.0) and PMT electrodes. Polymer coated electrodes were also used in an amperometric detector for flow injection analysis of HQ. The responses of the polymer electrode were 5–15 times larger as compared to those of bare platinum. PMT showed improved performance as an amperometric detector for flow injection analysis systems over other types of polymer electrodes. Detection limits as low as 1 × 10–9 M were achieved using the PMT, compared to 1 × 10–6 M using platinum electrodes.
In the present work, we have developed a sensitive platform for the selective determination of Hg(II) ions based on reduced graphene oxide (rGO) electrode modified with poly cysteine (Poly-Cys). The Poly-Cys/rGO modified electrode was characterised by SEM, ATR-IR and its electrochemical behaviour was investigated through cyclic voltammetry and square wave voltammetry. The synergistic effect of rGO and poly-cysteine favoured the complexation of Hg(II) ions onto the surface of the modified electrode. The ions were then anodically stripped and the corresponding voltammograms recorded. The process of complexation followed by stripping was repeated with increasing concentrations of the metal ion. The linear range for the electrochemical determination of Hg(II) using the modified electrode was found to be from 0.05 to 2.7 μM with a detection limit of 0.006 μM. In addition, the electrode also exhibited good stability with negligible sensitivity towards interfering metal ions. The analytical applicability of the modified electrode was investigated by carrying out mercury determination in water samples obtained from various sources.
In this paper sensitivity of a multilayer graphene nanoribbon (MGNR) interconnects parameters investigated. System sensitivity was studied on parameters like length and width in stable condition. The obtained results show with increasing width and length sensitivity will decrease and increase respectively. Impulse response diagram results show with increasing 50% width sensitivity will be zero but with increasing 50% length amplitude will decrease and the time of setting will increase. On the other hand from step response of transfer function, both width and length increase cause more stability for a system but the width parameter will be better choices for manipulating the dimension of MLGNR to reach the stable system.
Fexofenadine has been assayed by two methods. Titration (given as Method A) and spectrophotometric (given as Method B) were two methods involved in the assay procedure. The proposed titrimetric technique depends on the oxidation of FFH with identified abundance of KMnO4 and uninvolved KMnO4 was dictated by reacting it with FAS whose molarity is 0.05 M. Response stoichiometry is observed to be 1:2 (FFH: potassium permanganate).
In this work, a new voltammetric biosensor, based on the encapsulation of laccase from Trametes versicolor in an electrodeposited nanocomposite film, was developed for the detection of catechol. The nanocomposite was composed of chitosan (CS) modified with trymiristine (Tr), both of natural origin, to enhance its conductivity. FTIR and SEM studies were performed to characterize the modified chitosan film and the encapsulation of the enzyme. The analytical performance of the elaborated biosensor was determined through voltammetry detection of the produced quinone. Catechol was detected in a linear range between 10–20 and 10–15 M and a sensitivity of 0.4667 mA/p [catechol] was found. The repeatability of this biosensor is good as its RSD is equal to 1.35% and it shows stability for four weeks. To test the functionality of the developed biosensor, the total phenolic content of three samples of natural oils was determined and compared to a colorimetric test.
Leptospirosis is a febrile illness caused by the Leptospira, which is a highly motile, spirochete threadlike thin rod bacteria having a hook-like structure on both ends. This causes nearly 58990 deaths worldwide every year. They are most commonly found in rodents and can be transferred by cuts and abrasions in the body, mucous membranes or conjunctivae, or aerosol inhalation of microscopic droplets. Entry in the body lead to entry in blood circulation, different organs will be targeted. This review article explains current methodologies for the detection of Leptospira and the need for an early diagnostic tool. Leptospirosis can be treated if diagnosed in the early stage of infection. This review article consists of current methodologies used for the detection of Leptospira, the advantages and disadvantages of the methods used. Moreover, the need for an early diagnostic tool for the exposure of Leptospirosis in the acute phase is given importance. Even though the gold standard method MAT is used for confirmatory, culture preservation and other things are hectic, laborious. Currently, the molecular techniques used for the early detection of Leptospira needs experienced personnel and sophisticated instrument for the performance which is quite challenging to be found in the rural or undeveloped places. The need for sciences to come together is mentioned, where the innovative collaboration of physical sciences like Nanotechnology meets Microbiology which will lead to the innovation of some highly specific tools for the detection of diseases. The review article contains the useful methodology for the cultivation and detection by the conventional method, which will bring out innovation by modifications or by generating ideas that can be used for the diagnosis.
In this work, we prepared AgOx/Graphene composite material as the working electrode; the acetaminophen is determined by the electrochemical method. Using cyclic voltammetry electrochemical sensing method determined the current signal of acetaminophen (0.98 μM–15.6 μM) with electrolyte phosphate-buffer solution. When the voltage was operated as 0.42 V, an oxidation peak appeared in the linear concentration range and the least mean square was obtained R2 = 0.9922, and the detection limit was calculated as 0.26 μM. Using a differential pulse voltammetry electrochemical-sensing method, we determined the current signal of various acetaminophen concentrations (0.98 μM–7.8 μM). When the voltage is 0.33 V, R2 = 0.9996, and the detection limit is 0.15 μM. The material was characterized by TEM and XRD. It was also confirmed that Ag2O and Ag coexist (AgOx) on the surface of graphene, which facilitates the oxidation-reduction reaction of acetaminophen on the electrode.
Thermal conductivity and viscosity studies of carboxyl (–COOH) functionalized multi-walled carbon nanotubes-Silicone oil nanofluids were discussed in this work. Carboxyl (–COOH) functionalized MWCNT-Silicone oil nanofluids were prepared in various concentration ranges from 0.001 to 0.005 g of COOH-MWCNT and characterized at a range of temperatures between 303 K to 323 K. The thermal conductivity of carboxyl (–COOH) functionalized MWCNT-Silicone oil nanofluids increases with the raise in concentration of MWCNTs and also with the raise in temperatures. Mechanism for the enhancement of Silicone oil with concentration of MWCNT is due to the percolation of heat through the nanotubes through axial direction than through radial direction. Because of large aspect ratio of nanotubes heat transfer inside MWCNTs is also more. Also, as the temperature increases the viscosity of the (–COOH) functionalized MWCNT-Silicone oil nanofluids decreases, because CNT aggregation kinetics may contribute resulting in enhanced thermal conductivity.
Power dissipation and delay are the challenging issues in the design of VLSI circuits. This manuscript explores joint effect of Self-Bias transistors (SBTs) and Optimum Bulk Bias Technique (OBBT) on CMOS circuits. Earlier investigations on SBTs shows decrease in power dissipation of combinational as well as sequential circuits. We extend the analysis by studying the effect of OBBT on the static and dynamic power of CMOS circuits with SBTs coupled amid the pull-up/down network and the supply bars. Extensive SPICE simulations have been carried out in 0.18 μm technology. Results demonstrate that, a 73% drop in power in case of combinational circuits and 43% in case of sequential circuits can be accomplished by engaging OBBT in digital circuits. Trade-off between power and delay is also been presented.
Molecular interactions of Silicone oil based Beryllium oxide nanofluids have been studied using ultrasonic parameters at room temperature. BeO nanoparticles synthesized by chemical precipitation method was used to prepare silicone oil based BeO nanofluids. BeO nanofluids were prepared by dispersing synthesized BeO nanoparticles in the Silicone Oil base fluid with the help of sonication. Ultrasonic velocity for particle-fluid mixtures of Silicone oil with BeO has been carried out for different volume fraction (0 to 0.003) at 0.0005 intervals at room temperature. The data experimentally measured has been used to estimate the various acoustical and thermodynamical parameters. The behavior of these parameters in this particle fluid system has been discussed in terms of inter/intramolecular interactions with respect to concentration. The particle base fluid molecular interactions in the nanofluids cause an increment in velocity value of Silicone oil based nanofluids. The propagation of ultrasonic waves causes impedance which increases the intermolecular distance between the molecules. The transmission and reflection modes of sound waves in the nanoparticle and base fluid molecules are noted by the specific acoustic impedance. It is noted that the acoustic impedance value increases with rise in concentration owing to the molecular interaction between BeO and silicone oil fluid molecules affecting the structural arrangement.
Lactometer is used to monitor milk quality at various dairy centers but this may lead towards incorrect results because it requires human intervention and exact temperature correction as well as overall process is time-consuming. Presented work proposes the multispectral based spectroscopic approach along with the comparative study of different chemometric and artificial neural network (ANN) based techniques to measure different milk quality parameters. A multispectral spectroscopic sensing module has been designed using off the shelf components and further interfaced with 8-bit microcontroller based embedded system to produce three different spectrums of transmittance and scattering at +90 degree and –90 degree over the wavelength range of 340–1030 nm. Data acquisition process has been performed for 150 milk samples (cow, buffalo, and mix) collected from the bulk milk cooling center (BMC), Jaipur. Different statistical modeling techniques such as principle component regression (PCR), multiple linear regression (MLR) and partial least square regression (PLSR) have been implemented to develop correlation models between extracted features and target milk parameters. Implemented techniques have been compared based on the accuracy of their prediction models and it has been observed that PLSR shows better results compared to other two techniques. ANN-based modeling approach also has been explored to improve the accuracy of results. Five different artificial neural networks (ANN) based modeling techniques (LevenbergMarquardt, Bayesian regulation, scaled conjugate gradient, gradient descent and resilient) have been used to predict targeted milk quality parameters. Out of them, Gradient descent modeling technique performs better to predict fat content of the milk (R2 = 0.96198), Bayesian regulation performs better to predict lactose content (R2 = 0.90594) and others (solid non-fat (SNF), protein) are just satisfactory (R2 = 0.76077 for SNF using scaled conjugate gradient, R2 = 0.41935 for protein using Levenberg Marquardt). Produced results are validated with the MilkoScan FT1 system installed at Rajasthan Corporation of Dairy Federation (RCDF), Jaipur and it has been observed that results presented higher order of coefficient of determination as mentioned above (except protein, S.N.F.). A smartphone-based android application also has been developed to acquire data from the embedded system using Bluetooth protocol and transfer to cloud with the location information for further analysis.
The aim of this work is recovery the chromium content from the tannery wastewater to decrease the environmental pollution. Also, benefit the extracted chromium compound by study their electrical behavior to be used as humidity sensor device. The chromium content was extracted as a solid power by using MgO for precipitation. The prepared dry powder was characterized by different process. The results of the characterizations indicate that the chromium content precipitated as MgCr2O4. The efficiency of separation reaches to 99.98%. The crystalline size was calculated by applying Scherer equation, the calculation indicate that the MgCr2O4 formed in nano-sized particles and affected markedly with calcinations. As the calcination temperatures increase from 300 to 900 °C the crystalline size increases from 44.1 to 70.6 nm, this may due to growth the crystals by calcinations. To study the evaluation of MgCr2O4 as relative humidity (RH) sensors, the dried samples were exposed to different humidities between 22 to 92%. The electrical behaviors of humidity samples were measured to investigate the humidity sensing. AC conductivity of both the dry and the humidity samples indicate that the conductivity increases as the humidity increase from 27 to 80 RH%. The variation of conductivity for both dried and humidity samples shows that as the humidity increases from 22 to 80, the conductivity increases while above 80% the conductivity greatly increase. From the dependence of the electrical properties of MgCr2O4 on water content, it may conclude that, MgCr2O4 can be used as humidity sensors between 27 to 90%.
Herein, we report the fabrication of electrochemical sensor for the detection of mercury Hg(II) ions using macroporous divinyl benzene immobilized on ion-exchange polymeric ionophore. Impedance spectroscopy was adopted to examine the performance of the fabricated sensor. Various experiments were done to get the optimized experimental conditions of the fabricated sensor. The fabricated sensor demonstrates a linear range of 10 –8 to 10 –5 M and low detection limit was about 10 –4.8 M.
This paper aims to discuss a comprehensive survey on clustering algorithms for wireless sensor networks (WSN). The several real-time applications adopted the WSN with the advance features. But the capacity and size of the battery used in the sensor nodes are limited. Battery replacement or recharging is very difficult in most outdoor applications. Hence handling this kind of network is one of the issues. One of the best solutions to the energy issue is Clustering. Clustering is to balance the energy consumption of the whole network by cluster-based architecture to prolong the network lifetime. Sensor nodes grouped into clusters; one sensor node selects as the cluster head for each cluster. The cluster head sensor node collects the data from their sensor member nodes and forwards them to the sink node. In cluster-based architecture, cluster formation and the selection of the cluster head node decides the network lifetime. The paper discusses the for and against various clustering algorithms. It suggests the vital parameters for developing energy-efficient clustering algorithms and steps to overcome the limitations.
This paper presents an ultra low power process-insensitive two stage CMOS OP-AMP employing bulk-biasing technique realised in a standard 45 nm CMOS technology. Bulk-Biasing technique has been employed to augment the DC gain of two stage CMOS OP-AMP without having any impact on its power dissipation and output swing. In this work, high gain-bandwidth product (GBW) with appropriate phase margin is achieved through pseudo-cascode compensation approach which overcomes the drawbacks of Miller compensation technique also. Furthermore, the effect of width scaling on performance metrics of proposed OP-AMP has been analysed. The designed OP-AMP exhibits enhanced DC gain of 94.2 dB, gain-bandwidth product (GBW) of 460 MHz and adequate phase margin of 80°; with fast settling response. Also, the proposed OP-AMP has power dissipation of 27 μW and leakage current of 6.4 pA only. The design and optimisation of proposed OP-AMP is carried out at a power supply of 0.7 V under room temperature in Cadence Virtuoso tool.
Milk analyzer is a very useful instrument in the dairy industry. Feed is the principle cause of variation in the composition of fat, although several other factors are believed to influence. The fat concentration is most sensitive to dietary changes, followed by protein concentration; whereas the concentration of lactose, vitamins, Solid not fat (SNF), salts and other solid constituents do not respond to the dietary alterations. Analyzing the percentage of fat, SNF, protein and lactose are very important. There are two different type of milk analyzers are reported in this work. Both are low cost and user friendly milk analyzer. One is a milk analyzer using a constant phase element (CPE) sensor and it is a contact type. The other one is milk analyzer using ultrasound wave. The ultrasonic sensor is a noncontact type sensor. When ultrasound wave passed through the milk sample it is attenuated. The signal conditioning circuit is designed and the performance of milk analyzer is studied in this work. These two milk analyzers are inexpensive and easy to handle.
The aim of this study was to evaluate the efficacy of Allium sativum in Swiss albino mice against DLA induced. Experimental animals were fed with A. sativum extract, orally for 7 alternative day's. Results shown that A. sativum treated to inhibit the Tumor Necrosis factor alpha (TNF-α) expression due to the presence of sulfur compounds. Concurrently A. sativum extract significantly increases the hemoglobin level and decrease the serum glutamic oxaloacetic transaminase (SGOT) serum glutamate pyruvate transaminase (SGPT) alkaline phosphatase (ALP) and gamma glutamyltransferase levels (γ-GT). The Studies implied that natural compounds have antiinflammatory action.
In this work, microwires of gold nanoparticles (Au NPs) were grown using the fungusAspergillus nigeras a biological template. Au NPs were synthesized through the reduction of chloroauric acid using monosodium glutamate (MSG) in an aqueous media. The MSG here, served as a nutritional trigger behind the self-organization of Au NPs onAspergillus nigerapart from being the reducing as well as stabilizing agent. The fungal hyphae coated with gold nanoparticles were spread over the glass slide. The ZnO/ZnS core/shell nanostructures were deposited in a 2 mm gap of gold microwires’ spread. Uric acid sensing behavior of these ZnO/ZnS core/shell nanostructures were studied using the gold microwires as electrode.
The work presented here, the flash synthesis of high photoluminescence of CdSe/CdS Dot-in-Rods was carried out by "high-temperature short-time" (HTST) processing technique of quantum yield being 77%. Upon characterization by transmission electron microscope (TEM), it is found to be the dimensions of CdSe-CdS QDs to be rods (rod length rod diameter) of 27.8 × 3.4 nm. A layer of high luminescence CdSe/CdS Dot-in-Rods was grown on the surface of the touch sensitive natural Mimosa pudica (MP) natural conducting fiber by chemical dipping method. The composite CdSe/CdS are made up of a CdSe spherical core (Dot) of average diameter about 2.9 nm embedded in a Rod of CdS shell. The well-oriented CdSe/CdS Dot-in-Rods nano-particle was observed to have an emission peak at 545 nm. The works suggest a sensing plate which enhances Photoluminescence potential of conducting natural fiber.
The purpose of this work is to analyse Cu, Zn, Pb and Cd simultaneously in biological samples such as serum, hair, tooth and bone using differential pulse stripping voltammetry (DPSV). Therefore, suitable sample preparation and experimental conditions are determined. Trace metal concentrations of biological samples are measured and compared with the literature values. Cu, Zn and Pb are found in hair, tooth and bone samples while Cu and Zn metals is found in serum sample.
