Improving circuit miniaturization and its efficiency using Rough Set Theory

High-speed, accuracy, meticulousness and quick response are notion of the vital necessities for modern digital world. An efficient electronic circuit unswervingly affects the maneuver of the whole system. Different tools are required to unravel different types of engineering tribulations. Improving the efficiency, accuracy and low power consumption in an electronic circuit is always been a bottle neck problem. So the need of circuit miniaturization is always there. It saves a lot of time and power that is wasted in switching of gates, the wiring-crises is reduced, cross-sectional area of chip is reduced, the number of transistors that can implemented in chip is multiplied many folds. Therefore to trounce with this problem we have proposed an Artificial intelligence (AI) based approach that make use of Rough Set Theory for its implementation. Theory of rough set has been proposed by Z Pawlak in the year 1982. Rough set theory is a new mathematical tool which deals with uncertainty and vagueness. Decisions can be generated using rough set theory by reducing the unwanted and superfluous data. We have condensed the number of gates without upsetting the productivity of the given circuit. This paper proposes an approach with the help of rough set theory which basically lessens the number of gates in the circuit, based on decision rules.Comment: The International Conference on Machine Intelligence Research and Advancement,ICMIRA-201

Graphene oxide for electrochemical sensing applications

By exploiting the presence of abundant carboxylic groups (–COOH) on graphene oxide (GO) and using EDC–NHS (1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride–N-hydroxysuccinimide) chemistry to covalently conjugate protein molecules, we demonstrate a novel electrochemical immunosensor for detection of antibody–antigen (Rabbit IgG–AntiRabbit IgG) interactions. The interactions were verified using Electrochemical Impedance Spectroscopy (EIS). Although GO is known to be a poor conductor, the charge transfer resistance (RP) of a GO modified glassy carbon electrode (GCE) was found to be as low as 1.26 Ω cm2. This value is similar to that obtained for reduced graphene oxide (RGO) or graphene and an order of magnitude less than bare GCE. The EIS monitored antibody–antigen interactions showed a linear increase in RP and the overall impedance of the system with increase of antibody concentration. Rabbit IgG antibodies were detected over a wide range of concentrations from 3.3 nM to 683 nM with the limit of detection (LOD) estimated to be 0.67 nM. The sensor showed high selectivity towards Rabbit IgG antibody as compared to non-complementary myoglobin. RGO modified GCE showed no sensing properties due to the removal of carboxylic groups which prevented subsequent chemical functionalization and immobilization of antigen molecules. The sensitivity and selectivity achievable by this simple label free technique hint at the possibility of GO becoming the electrode material of choice for future electrochemical sensing protocols

Experimental and numerical investigation of capillary flow in SU8 and PDMS microchannels with integrated pillars

Microfluidic channels with integrated pillars are fabricated on SU8 and PDMS substrates to understand the capillary flow. Microscope in conjunction with highspeed camera is used to capture the meniscus front movement through these channels for ethanol and isopropyl alcohol, respectively. In parallel, numerical simulations are conducted, using volume of fluid method, to predict the capillary flow through the microchannels with different pillar diameter to height ratio, ranging from 2.19 to 8.75 and pillar diameter to pitch ratio, ranging from 1.44 to 2.6. The pillar size (diameter, pitch and height) and the physical properties of the fluid (surface tension and viscosity) are found to have significant influence on the capillary phenomena in the microchannel. The meniscus displacement is non-uniform due to the presence of pillars and the non-uniformity in meniscus displacement is observed to increase with decrease in pitch to diameter ratio. The surface area to volume ratio is observed to play major roles in the velocity of the capillary meniscus of the devices. The filling speed is observed to change more dramatically under different pillar heights upto 120 mu m and the change is slow with further increase in the pillar height. The details pertaining to the fluid distribution (meniscus front shapes) are obtained from the numerical results as well as from experiments. Numerical predictions for meniscus front shapes agree well with the experimental observations for both SU8 and PDMS microchannels. It is observed that the filling time obtained experimentally matches very well with the simulated filling time. The presence of pillars creates uniform meniscus front in the microchannel for both ethanol and isopropyl alcohol. Generalized plots in terms of dimensionless variables are also presented to predict the performance parameters for the design of these microfluidic devices. The flow is observed to have a very low Capillary number, which signifies the relative importance of surface tension to viscous effects in the present study