In a world facing climate change and environmental degradation, it is more important than ever to develop sustainable energy sources. For electricity, which fuels many activities from transportation to cloud services, its sustainable production and storage is important to fight climate change and promote more egalitarian societies. Today frontline communities and individuals have the ability own and control the sources of renewable energy, such as solar energy.
Organic dye sensitized solar cells (ODSSCs) are a promising new technology for clean energy production. In this project, we will discuss economic and affordable energy production that could advance energy justice initiatives by applying artificial intelligence tools to the design of ODSSCS solar cells to find ecofriendly materials and solve pressing problems. We will use data science, visualization, and machine learning approaches to study a database of molecules for ODSSCs. These tools will be used to explore molecular data sets and identify trends, along with discussing the validity of the data sources. Furthermore, we will analyze molecular descriptors and apply machine learning to predict properties of unknown molecules for future solar cells.
Project Leaders and Trainers:
Alvaro Vazquez-Mayagoitia
Image source: https://sinovoltaics.com/solar-basics/solar-cell-guide-part-4-organic-and-dye-sensitized-solar-cells/