Using the cuckoo algorithm to improve perovskite solar cell performance (Development Engineering Conferences Center Articles Database, 2025)
The cuckoo algorithm, inspired by the brood parasitism of cuckoo birds, has shown promising results in optimizing the performance of perovskite solar cells (PSCs). By mimicking the natural selection process, the cuckoo algorithm efficiently searches for optimal solutions in complex problem spaces. It has been utilized to fine-tune various parameters in PSCs, such as material composition, layer thickness, and fabrication processes. This optimization leads to improved light absorption, charge transport, and overall device stability. Specifically, the algorithm helps in identifying the most effective perovskite composition and the best architecture for the solar cells, resulting in significant enhancements in power conversion efficiency (PCE). Studies have reported that the application of the cuckoo algorithm can boost the efficiency of perovskite solar cells by up to 20-25%, So that its efficiency is between 25-30%. This improvement is a substantial step forward in making PSCs more competitive with traditional silicon-based solar cells and other emerging photovoltaic technologies.