Nanofibers of Polyaniline and Cu(II)-l-Aspartic Acid for a Room-Temperature Carbon Monoxide Gas Sensor.

In the present study, the carbon monoxide (CO) sensing property of Cu(II)-l-aspartic acid nanofibers/polyaniline (PANI) nanofibers composite was investigated at room temperature. The nanofiber composite was formed through the ultrasound mixing of emeraldine salt PANI nanofibers and Cu(II)-l-aspartic acid nanofibers, which were synthesized by using a polymerization process and simple self-assembly method, respectively. The nanofibers composite demonstrated a branched structure in which the Cu(II)-l-aspartic acid nanofiber framework is similar to the trunk of a tree and the polyaniline nanofibers is like its branches. It seems that this special structure and one-dimension/one-dimension interface are suitable for gas adsorption and sensing. The performance of the prepared sensor toward CO gas was investigated at room temperature in a wide concentration range (200-8000 ppm). The experimental results indicate that the incorporation of amino acid-based copper metal-biomolecule framework nanofibers to PANI nanofibers enhances the response value (12.41% to 4000 ppm), yielding good selectivity and acceptable response and recovery characteristics (220 s/240 s) at room temperature. The detection limit of Cu(II)-l-aspartic acid nanofibers/PANI nanofibers sensor for carbon monoxide is obtained at 120 ppm.

Simultaneous determination of hydroquinone and catechol at gold nanoparticles mesoporous silica modified carbon paste electrode.

A new electrochemical sensor based on gold nanoparticles mesoporous silica modified carbon paste electrode (AuNPs-MPS) was developed for simultaneous determination of hydroquinone and catechol. Morphology and structure of the AuNPs-MPS were characterized by transmission electron microscopy, X-ray diffraction and Fourier transform infrared spectroscopy. The electrochemical behavior of hydroquinone and catechol were investigated using square wave voltammetry and the results indicate that the electrochemical responses are improved significantly at the modified electrode. The observed oxidative peaks separation of about 120mV made possible the simultaneous determination of hydroquinone and catechol in their binary-mixture. Under the optimized condition, a linear dynamic range of 10.0µM-1.0mM range for hydroquinone with the detection limit of 1.2µM and from 30.0µM-1.0mM for catechol with the detection limit of 1.1µM were obtained. The applicability of the method was demonstrated by the recovery studies of hydroquinone and catechol in spiked tap water samples.

Simultaneous determination of tyrosine and tryptophan by mesoporous silica nanoparticles modified carbon paste electrode using H-point standard addition method.

A simple, selective and sensitive sensor based on mesoporous silica nanoparticles modified carbon paste electrode (MSNs/CPE) is introduced for electrochemical determination of tyrosine (Tyr) and tryptophan (Trp). Compared with the unmodified electrode and commercial SiO2 modified electrode (SiO2/CPE), the oxidation peak current significantly improved for both amino acids. Under optimized experimental conditions, the oxidation peak current of Trp was linear over a concentration range of 5.0 × 10(-8) to 4.0 × 10(-4) M with a detection limit of 3.4 × 10(-8) M. The oxidation peak current of Tyr was linear over a concentration range from 5.0 × 10(-7) to 6.0 × 10(-4) M with a detection limit of 1.5 × 10(-7) M. For simultaneous determination Trp and Tyr, H-point standard addition method was applied to resolve the overlapping of differential pulse voltammetric peaks of Trp and Tyr. The results showed that the method was successfully applied to the simultaneous determination of Trp and Tyr in some synthetic samples. Moreover, the applicability of the method was demonstrated by the recovery tests of Trp and Tyr in artificial urine.

Fluorescence Determination of Warfarin Using TGA-capped CdTe Quantum Dots in Human Plasma Samples.

In this study, some effort has been performed to provide low temperature, less time consuming and facile routes for the synthesis of CdTe quantum dots using ultrasound and water soluble capping agent thioglycolic acid. TGA-capped CdTe quantum dots were characterized through x-ray diffraction, transmission electron microscopy, Fourier transform infrared, ultraviolet-visible and fluorescence spectroscopy. The prepared quantum dots were used for warfarin determination based on the quenching of the fluorescence intensity in aqueous solution. Under the optimized conditions, the linear range of quantum dots fluorescence intensity versus the concentration of warfarin was 0.1-160.0 µM, with the correlation coefficient of 0.9996 and a limit of detection of 77.5 nM. There was no interference to coexisting foreign substances. The selectivity of the sensor was also tested and the results show that the developed method possesses a high selectivity for warfarin.

Effect of covalent attachment of neomycin on conformational and aggregation properties of catalase.

The carboxylic groups of glutamic acid and aspartic acid residues of catalase (CAT) were chemically modified using the treatment of the enzyme with 1-ethyl-3-(3'-dimethylamino) carbodiimide hydrochloride (EDC) and neomycin. The effect of covalent attachment of neomycin on the enzymatic activity, conformational and aggregation properties of CAT was investigated. The modification of CAT with different concentrations of neomycin showed two different types of behavior, depending up on the concentration range of neomycin. In the concentration range from 0.0 to 5.2 mM, neomycin-modified CAT, compared to the native enzyme exhibited higher a-helix content, reduced surface hydrophobicity, little enhancement in CAT activity and a better protection against thermal aggregation, whereas at concentrations greater than 5.2 mM, the modified enzyme exhibited a significant decrease in CAT activity and an increase in random coil content which may result in disorder in the protein structure and increase in thermal aggregation. This modification is a rapid and simple approach to investigate the role of aspartate and glutamate residues in the structure, function and folding of CAT.

A sensitive electrochemical sensor for determination of gallic acid based on SiO2 nanoparticle modified carbon paste electrode.

Gallic acid (GA), one of the main phenolic components, has been a subject of increasing interest due to their biological properties, including anti-inflammatory, antihistaminic, and antitumor activities, scavenging of free radicals, and protecting against cardiovascular diseases. Therefore, developing sensitive and selective sensor for GA is very important and interesting. Herein, SiO2 nanoparticles were synthesized and then used to prepare a modified carbon paste electrode (CPE) for determination of GA. For better comparison, multiwalled carbon nanotubes (MWCNTs) and graphite were also employed to prepare an electrochemical sensor for determination of GA. The electrochemical behaviors of GA at different electrochemical sensors were investigated. Compared with other sensors, the SiO2 nanoparticle sensor greatly enhances the response signal of GA due to the large active surface area and high accumulation efficiency. Voltammetric studies show that the SiO2 nanoparticle modified carbon paste electrode is sensitive to GA in the concentration range of 8.0 × 10(-7) to 1.0 × 10(-4) mol L(-1), and the limit of detection and sensitivity were calculated as 2.5 × 10(-7) mol L(-1) and 1790.7 (µA/mM), respectively. Finally, the proposed electrochemical sensor was successfully employed to determine GA in tea and orange juice samples.

Artificial neural network-genetic algorithm based optimization for the adsorption of methylene blue and brilliant green from aqueous solution by graphite oxide nanoparticle.

In this study, graphite oxide (GO) nano according to Hummers method was synthesized and subsequently was used for the removal of methylene blue (MB) and brilliant green (BG). The detail information about the structure and physicochemical properties of GO are investigated by different techniques such as XRD and FTIR analysis. The influence of solution pH, initial dye concentration, contact time and adsorbent dosage was examined in batch mode and optimum conditions was set as pH=7.0, 2 mg of GO and 10 min contact time. Employment of equilibrium isotherm models for description of adsorption capacities of GO explore the good efficiency of Langmuir model for the best presentation of experimental data with maximum adsorption capacity of 476.19 and 416.67 for MB and BG dyes in single solution. The analysis of adsorption rate at various stirring times shows that both dyes adsorption followed a pseudo second-order kinetic model with cooperation with interparticle diffusion model. Subsequently, the adsorption data as new combination of artificial neural network was modeled to evaluate and obtain the real conditions for fast and efficient removal of dyes. A three-layer artificial neural network (ANN) model is applicable for accurate prediction of dyes removal percentage from aqueous solution by GO following conduction of 336 experimental data. The network was trained using the obtained experimental data at optimum pH with different GO amount (0.002-0.008 g) and 5-40 mg/L of both dyes over contact time of 0.5-30 min. The ANN model was able to predict the removal efficiency with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) at hidden layer with 10 and 11 neurons for MB and BG dyes, respectively. The minimum mean squared error (MSE) of 0.0012 and coefficient of determination (R(2)) of 0.982 were found for prediction and modeling of MB removal, while the respective value for BG was the MSE and R(2) of 0.001 and 0.981, respectively. The ANN model results show good agreement with experimental data.

Construction of a new selective coated disk electrode for Ag (I) based on modified polypyrrole-carbon nanotubes composite with new lariat ether.

A poly (vinyl chloride) (PVC) matrix membrane ion-selective electrode for silver (I) ion is fabricated based on modified polypyrrole - multiwalled carbon nanotubes composite with new lariat ether. This sensor has a Nernstian slope of 59.4±0.5mV/decade over a wide linear concentration range of 1.0×10(-7) to 1.0×10(-1)molL(-1) for silver (I) ion. It has a short response time of about 8.0s and can be used for at least 50days. The detection limit is 9.3×10(-8)molL(-1) for silver (I) ion, and the electrode was applicable in the wide pH range of 1.6 -7.7. The electrode shows good selectivity for silver ion against many cations such as Hg (II), which usually imposes serious interference in the determination of silver ion concentration. The use of multiwalled carbon nanotubes (MWCNTs) in a polymer matrix improves the linear range and sensitivity of the electrode. In addition by coating the solid contact with a layer of the polypyrrole (Ppy) before coating the membrane on it, not only did it reduce the drift in potential, but a shorter response time was also resulted. The proposed electrode was used as an indicator electrode for potentiometric titration of silver ions with chloride anions and in the titration of mixed halides. This electrode was successfully applied for the determination of silver ions in silver sulphadiazine as a burning cream.

Application of silver nanoparticles and principal component-artificial neural network models for simultaneous determination of levodopa and benserazide hydrochloride by a kinetic spectrophotometric method.

A multicomponent analysis method based on principal component analysis-artificial neural network model (PC-ANN) is proposed for the simultaneous determination of levodopa (LD) and benserazide hydrochloride (BH). The method is based on the reaction of levodopa and benserazide hydrochloride with silver nitrate as an oxidizing agent in the presence of PVP and formation of silver nanoparticles. The reaction monitored at analytical wavelength 440 nm related to surface plasmon resonance band of silver nanoparticles. Differences in the kinetic behavior of the levodopa and benserazide hydrochloride were exploited by using principal component analysis, an artificial neural network (PC-ANN) to resolve concentration of analytes in their mixture. After reducing the number of kinetic data using principal component analysis, an artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. The optimized ANN allows the simultaneous determination of analytes in mixtures with relative standard errors of prediction in the region of 4.5 and 6.3 for levodopa and benserazide hydrochloride respectively. The results show that this method is an efficient method for prediction of these analytes.

Sodium dodecyl sulfate coated alumina modified with a new Schiff's base as a uranyl ion selective adsorbent.

A simple and selective method was used for the preconcentration and determination of uranium(VI) by solid-phase extraction (SPE). In this method, a column of alumina modified with sodium dodecyl sulfate (SDS) and a new Schiff's base ligand was prepared for the preconcentration of trace uranyl(VI) from water samples. The uranium(VI) was completely eluted with HCl 2M and determined by a spectrophotometeric method with Arsenazo(III). The preconcentration steps were studied with regard to experimental parameters such as amount of extractant, type, volume and concentration of eluent, pH, flow rate of sample source and tolerance limit of diverse ions on the recovery of uranyl ion. A preconcentration factor more than 200 was achieved and the average recovery of uranyl(VI) was 99.5%. The relative standard deviation was 1.1% for 10 replicate determinations of uranyl(VI) ion in a solution with a concentration of 5 µg mL(-1). This method was successfully used for the determination of spiked uranium in natural water samples.

Optical detection of phenolic compounds based on the surface plasmon resonance band of Au nanoparticles.

An indirect colorimetric method is presented for detection of trace amounts of hydroquinone (1), catechol (2) and pyrogallol (3). The reduction of AuCl4(-) to Gold nanoparticles (Au-NPs) by these phenolic compounds in the presence of cetyltrimethylammonium chloride (CTAC) produced very intense surface plasmon resonance peak of Au-NPs. The plasmon absorbance of Au-NPs allows the quantitative colorimetric detection of the phenolic compounds. The calibration curves derived from the changes in absorbance at lambda = 568 nm were linear with concentration of hydroquinone, catechol and pyrogallol in the range of 7.0 x 10(-7) to 1.0 x 10(-4)M, 6.0 x 10(-6) to 2.0 x 10(-4)M and 6.0 x 10(-7) to 1.0 x 10(-4)M, respectively. The detection limits were 5.3 x 10(-7), 2.5 x 10(-6) and 3.2 x 10(-7)M for the hydroquinone, catechol and pyrogallol, respectively. The method was applied satisfactorily to the determination of phenolic compounds in water samples and pharmaceutical formulations.