Escherichia coli bacteria detection by using graphene-based biosensor.

Graphene is an allotrope of carbon with two-dimensional (2D) monolayer honeycombs. A larger detection area and higher sensitivity can be provided by graphene-based nanosenor because of its 2D structure. In addition, owing to its special characteristics, including electrical, optical and physical properties, graphene is known as a more suitable candidate compared to other materials used in the sensor application. A novel model employing a field-effect transistor structure using graphene is proposed and the current-voltage (I-V) characteristics of graphene are employed to model the sensing mechanism. This biosensor can detect Escherichia coli (E. coli) bacteria, providing high levels of sensitivity. It is observed that the graphene device experiences a drastic increase in conductance when exposed to E. coli bacteria at 0-10(5) cfu/ml concentration. The simple, fast response and high sensitivity of this nanoelectronic biosensor make it a suitable device in screening and functional studies of antibacterial drugs and an ideal high-throughput platform which can detect any pathogenic bacteria. Artificial neural network and support vector regression algorithms have also been used to provide other models for the I-V characteristic. A satisfactory agreement has been presented by comparison between the proposed models with the experimental data.

Sensing and identification of carbon monoxide using carbon films fabricated by methane arc discharge decomposition technique.

Carbonaceous materials have recently received attention in electronic applications and measurement systems. In this work, we demonstrate the electrical behavior of carbon films fabricated by methane arc discharge decomposition technique. The current-voltage (I-V) characteristics of carbon films are investigated in the presence and absence of gas. The experiment reveals that the current passing through the carbon films increases when the concentration of CO2 gas is increased from 200 to 800 ppm. This phenomenon which is a result of conductance changes can be employed in sensing applications such as gas sensors.

Simultaneous microemulsion liquid chromatographic analysis of fat-soluble vitamins in pharmaceutical formulations: optimization using genetic algorithm.

An environmentally benign and simple method has been proposed for separation and determination of fat-soluble vitamins using isocratic microemulsion liquid chromatography. Optimization of parameters affecting the separation selectivity and efficiency including surfactant concentration, percent of cosurfactant (1-butanol), and percent of organic oily solvent (diethyl ether), temperature and pH were performed simultaneously using genetic algorithm method. A new software package, MLR-GA, was developed for this purpose. The results indicated that 73.6mM sodium dodecyl sulfate, 13.64% (v/v) 1-butanol, 0.48% (v/v) diethyl ether, column temperature of 32.5 degrees C and 0.02M phosphate buffer of pH 6.99 are the best conditions for separation of fat-soluble vitamins. At the optimized conditions, the calibration plots for the vitamins were obtained and detection limits (1.06-3.69microgmL(-1)), accuracy (recoveries>94.3), precision (RSD<3.96) and linearity (0.01-10mgmL(-1)) were estimated. Finally, the amount of vitamins in multivitamin syrup and a sample of fish oil capsule were determined. The results showed a good agreement with those reported by manufactures.