Geometric Shape Optimization of Organic Solar Cells for Efficiency Enhancement by Neural Networks

The complexity of the heterojunction organic solar cell stems from the delicate balance that exists between the different properties of the materials used and the geometric structure of the cell itself. Therefore several parameters affect the solar cell conversion efficiency. For this reason, in the literature there are a large variety of optimization techniques in order to improve the conversion efficiency of solar cells. Often these optimization techniques are complex and costly. In this paper, a back propagation neural network is used to disclose the link between length and the maximum power output of the device. The simulation results obtained show that the devices length has a great influence on the their efficiency and therefore must be taken into account in manufacturing processes.