A circuit model for defective bilayer graphene transistors

This paper investigates the behaviour of a defective single-gate bilayer graphene transistor. Point defects were introduced into pristine graphene crystal structure using a tightly focused helium ion beam. The transfer characteristics of the exposed transistors were measured ex-situ for different defect concentrations. The channel peak resistance increased with increasing defect concentration whilst the on–off ratio showed a decreasing trend for both electrons and holes. To understand the electrical behaviour of the transistors, a circuit model for bilayer graphene is developed which shows a very good agreement when validated against experimental data. The model allowed parameter extraction of bilayer transistor and can be implemented in circuit level simulators.<br/

Graphene FET circuit-level device modelling

This thesis presents models for a graphene based field effect transistor (GFET). The graphene material has been widely studied since its synthesis in 2004 and the material holds promise for the next generation electronic applications. Therefore, there is a need to model its device characteristics.In this respect the contributions presented here are, firstly, a SPICE-compatible model for both dual gate and single gate graphene transistors. The derivation of the carrier transport of both hole and electron conduction results in a set of analytical equations. These derivations cover the three identified regions of operation as well as the boundary voltage conditions that define the regions. The Jacobian entries are shown to be continuous across the region boundaries.Secondly, circuit levels model of a single-layer GFET and multi layer GFET suitable for a direct implementation in SPICE. In this contribution, a more accurate threshold voltage compared to other models is derived. This contribution also shows how models can be extended to as many layers the graphene channelled transistor has.Finally, the introduction of a thermionic resistance, which is modelled in parallel with the resistance due to gate induced charges, provides a model for the temperature dependent channel resistance. The contribution goes further to derive equations between the off current and the vertical electric fields. Thus, giving a good estimation of the tunable bandgap opening in graphene.The models in this contributions are validated against experimentally measured transistor characteristics which have been carried out by other research groups and the models show a good agreement in all cases validated. The thesis equally presents the use of a floating gate to optimize the transistors characteristics. To illustrate these contributions, algorithms of the models have been implemented on the following CAD tools, HSPICE, VHDL-AMS and Berkeley SPICE. During the course of this work one journal and five conference papers have been published

Inhibitory activity of seed extract from Picralima nitida, (Staph) on &beta;-D-glucosidase

The rate of hydrolysis of p- nitrophenyl &#946;-D- glucopyranoside (PNPG) by &beta;-D glucosidase (&beta;-D-glucoside glucohydrolase, E.C. 2.1.21) from African giant snail (Achatina achatina) has been studied in the presence of seed extracts from Picralima nitida (Staph) Th&H.D. A at a substrate concentration range of 0.04-0.2mM there was no product (P- nitrophenol) inhibition of the enzyme. The Km and Vmax values for PNPG were calculated from Line Weaver-Burk plots and the values obtained were 0.214mM and 125-nmol/mg protein/min respectively. &beta;-glucosidase from Achatina achatina degraded PNPG faster than, that from such as Aspergillus niger Humicola grisea and Geotricum. spp The alkaloid extracts from the mature seeds of Picralima nitida inhibited the enzyme in a competitive manner with inhibitor equilibrium constant (ki) values of 0.263, 0.157.0.125 and 0.10mg/1 for alkaloid (inhibitor) concentrations of 4,6,8 and 10mg./l respectively. The biochemical implication of this study is that since the seeds extract showed inhibition of enzyme activity, the exploitation of this potential could be of immense value in the current search for new therapeutically effective drugs with inhibitory effects against &beta;-glucosidae which is implicated in HIV infectivity of cells. Key Words: &beta;-D-glucosidase, P. nitida, inhibition, HIV infectivity Biokemistri Vol.16(2) 2004: 72-7

A hybrid smell agent symbiosis organism search algorithm for optimal control of microgrid operations.

This paper presents a hybrid Smell Agent Symbiosis Organism Search Algorithm (SASOS) for optimal control of autonomous microgrids. In microgrid operation, a single optimization algorithm often lacks the required balance between accuracy and speed to control power system parameters such as frequency and voltage effectively. The hybrid algorithm reduces the imbalance between exploitation and exploration and increases the effectiveness of control optimization in microgrids. To achieve this, various energy resource models were coordinated into a single model for optimal energy generation and distribution to loads. The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. The development of SASOS comprises components of Symbiotic Organism Search (SOS) and Smell Agent Optimization (SAO) codified in an optimization loop. Twenty-four standard test function benchmarks were used to evaluate the performance of the algorithm developed. The experimental analysis revealed that SASOS obtained 58.82% of the Desired Convergence Goal (DCG) in 17 of the benchmark functions. SASOS was implemented in the Microgrid Central Controller (MCC) and benchmarked alongside standard SOS and SAO optimization control strategies. The MATLAB/Simulink simulation results of the microgrid load disturbance rejection showed the viability of SASOS with an improved reduction in Total Harmonic Distortion (THD) of 19.76%, compared to the SOS, SAO, and MCC methods that have a THD reduction of 15.60%, 12.74%, and 6.04%, respectively, over the THD benchmark. Based on the results obtained, it can be concluded that SASOS demonstrates superior performance compared to other methods. This finding suggests that SASOS is a promising solution for enhancing the control system of autonomous microgrids. It was also shown to apply to other sectors of engineering optimization