Abstract: Advancing green energy technologies constitutes a core component of sustainable development strategies and has emerged as a crucial educational module in university chemistry curricula. Organic solar cells, with their distinctive advantages of lightweight construction, material flexibility, and scalable manufacturing potential, have developed into a significant technological pathway in renewable energy. This study presents an innovative experimental project that employs digital methodologies integrating artificial intelligence, high-throughput optical simulations, and digital twin technology. The project facilitates students’ comprehensive understanding of fundamental operational mechanisms in organic solar cells while promoting wider pedagogical adoption of such experiments. Through digitized human-computer interactions involving AI-assisted instruction, experimental parameter design, and data analysis, students acquire specialized knowledge of organic solar cells through hands-on practice, thereby enhancing autonomous learning and research capabilities. This approach contributes to talent development for the digitalized renewable energy sector. The experiment not only incorporates contemporary digital design elements but also provides a digital teaching framework for cultivating chemistry professionals.

Key words: Green energy, Organic solar cells, Artificial intelligence, Optical simulation, Digital twin