Researchers from the University of Bayreuth, Germany, including Pelin Çiloğlu, Carmen Tretmans, Carsten Deibel, Roderick MacKenzie, Roland Herzog, Jan-F. Pietschmann, and Martin Stoll, have developed a comprehensive computational model to study the performance of organic solar cells. Their work, published in the Journal of Computational Physics, aims to bridge the gap between theoretical predictions and experimental measurements in the field of organic photovoltaics (OPV).
Organic solar cells, which use organic materials to convert sunlight into electricity, offer several advantages over traditional silicon-based solar cells, such as flexibility, lightweight, and potentially lower production costs. However, their efficiency and performance can vary significantly due to the complex nanomorphology of the active layer where light absorption and charge separation occur. The researchers’ new model addresses this challenge by incorporating the dynamics of excitons—bound electron-hole pairs generated by light absorption—and their dissociation at bulk heterojunctions within the active layer.
The model utilizes realistic morphologies obtained from a detailed phase field model, which simulates the self-assembly of the organic materials. By combining this with a mathematical framework that describes the physical processes involved, the researchers can simulate the entire OPV device. To solve the complex, nonlinear system of equations that arises, they employ advanced numerical techniques, including finite element discretization and robust linear solvers. Three numerical schemes—Newton, Gummel, and Semi-Newton-Gummel—are used to efficiently simulate the device performance.
One of the key outcomes of this research is the ability to generate current-voltage curves that can be directly compared to experimental data. This capability is crucial for validating the model and ensuring that it accurately reflects the behavior of real-world OPV devices. By providing a reliable in silico tool, the researchers enable more efficient and cost-effective optimization of organic solar cells, potentially accelerating their development and commercialization.
For the energy industry, this research offers a powerful tool for understanding and improving the performance of organic photovoltaics. By simulating the behavior of OPV devices under various conditions, researchers and engineers can identify the most promising materials and device architectures, ultimately leading to more efficient and cost-effective solar energy solutions. This work highlights the importance of computational modeling in advancing renewable energy technologies and bringing them closer to widespread adoption.
This article is based on research available at arXiv.