Citation: Xiaotian Hu, Binhuan Qiu, Jinglin Le, Runrui Dai, Xiaolan Lü, Yu Hu. Digital Design, Computational Modeling, Fabrication and Characterization of Organic Solar Cells Based on Green Energy Principles[J]. University Chemistry, ;2026, 41(1): 298-309. doi: 10.12461/PKU.DXHX202506034 shu

Digital Design, Computational Modeling, Fabrication and Characterization of Organic Solar Cells Based on Green Energy Principles

Xiaotian Hu ^1,2,, ,
Binhuan Qiu ¹ ,
Jinglin Le ² ,
Runrui Dai ¹ ,
Xiaolan Lü ² ,
Yu Hu ^2,,,

1.
School of Ji Luan, Nanchang University, Nanchang 330031, China;
2.
School of Chemistry and Chemical Engineering, Nanchang University, Nanchang 330031, China

Corresponding author: Xiaotian Hu, Yu Hu,
Received Date: 10 June 2025
Revised Date: 9 September 2025

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.
- Green energy,
- Organic solar cells,
- Artificial intelligence,
- Optical simulation,
- Digital twin
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