In this paper the manufacture of an alkaline fuel cell electrodes made upfrom a Nano mesh (Pt:NiO) catalyst has been studying , made from a Nano mesh (Pt:NiO ) catalyst. The general morphology of the samples is were imaged by using with the an Atomic Force Microscope (AFM) to determine the roughness of the prepared surface, it constructed from nanostructure with dimensions in order of 35 nm. The Structural characteristics were studied through the analysis of X-ray diffraction (XRD) of the prepared nanomaterial for determining the yielding phase;1. 72 volt was also obtained at 0.02 A/cm2 current density for an alkaline fuel cell.

Microbial fuel cell is a device that uses the microorganism metabolism for the production of electricity under specific operating conditions. Double chamber microbial fuel cell was tested for the use of two cheap electrode materials copper and aluminum for the production of electricity under different operating conditions. The investigated conditions were concentration of microorganism (yeast) (0.5- 2 g/l), solutions temperature (33-45 ^oC) and concentration of glucose as a substrate (1.5- 6 g/l). The results demonstrated that copper electrode exhibit good performance while the performance of aluminum is poor. The electricity is generated with and without the addition of substrate. Addition of glucose substrate

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue