(177l) Development of Acceptor Materials for Organic Photovoltaic Devices through Computational Design

The steady increase in population and its strong dependence on fossil fuels have generated growing concern about the limited reserves of these resources and the adverse environmental impacts resulting from their indiscriminate and uncontrolled use. As a result, research is directed toward developing more efficient, sustainable, and clean alternatives to fossil fuels. Green energy, including solar, geothermal, wind, and heat, among others, has gained significant attention in recent decades since it is environmentally beneficial and has the potential to replace traditional energy sources.

Solar energy has become indispensable as an energy source because it is abundant, renewable, and environmentally friendly. Photovoltaic cells harness solar radiation by converting solar energy directly into electrical power to produce electricity or heat for various applications. There are several types of solar photovoltaic devices or solar cells. In this research, we focus on organic solar cells (OSC). Organic solar cells include thin film solar cell technologies, which employ organic materials or semiconducting organometallic compounds to absorb light. This photovoltaic technology has sparked widespread attention because of its lightweight design, flexibility, environmental stability, simplicity of manufacture, low cost, and semi-transparency. However, one of the main drawbacks of these devices is that they have lower power conversion efficiencies (PCE) than other types of solar cells.

Enhancing OSC performance requires addressing several factors, including improving donor and acceptor materials, optimizing device architecture, and enhancing stability and manufacturing techniques. In this study, our focus is on enhancing OSC active layers by identifying suitable materials.

Traditionally, the development or discovery of new materials was based on chemical intuition and trial-and-error approaches, which often proved inefficient and wasteful of resources. However, this old methodology has changed and has been gradually supplanted by silico design methodologies. These approaches use computer simulations, modeling, and data analysis to anticipate and evaluate quantitative structure-property relationships (QSPRs). We have used QSPR to assist the rational design of new for organic photovoltaic systems. This interest stems from the ability to construct and generate highly predictive models using molecular descriptors. Topological Molecular Computational designer (TOMOCOMD) 3D, technique was used to codify the chemical information in a set of acceptor materials. The molecular dataset was obtained from a bibliographic examination to create our database of PCE values and associated parameters such as: short-circuit current density (Jsc), open circuit voltage (Voc), and fill factor (FF).

Three models were successfully obtained for PCE, FF, and Jsc. The results suggest that the abovementioned technique might help generate a list of candidate acceptor molecules. However, more extensive research is needed to predict the Voc, as no relationship has been obtained. The most promising results will be selected for synthesis in our laboratory, and their real-world performance will be evaluated.