Illumination Time Dependent Learning in Dye Sensitized Solar Cells

Abstract

Learning through vision is an essential skill for intelligent machines. In an attempt to implement this highly complex feature at low energy cost, a dye-sensitized solar cell is proposed that learns using illumination time as a cue. Particularly, the device alters its photocurrent and memorizes this change in dependence of light exposure duration. This behavior parallels synaptic learning that also requires continuous or repeated electrical stimuli as triggers. Therefore, such optically learning solar cells may serve as promising building blocks in optoelectronic neural networks, potentially enabling visually learning electronics operating at negligible energy consumption and minimal hardware complexity.