Machine Learning Materials for Solar Energy

Project Details

Description

It has long been a dream to use the energy from the sun to generate enough electricity for everybody on earth. Novel hybrid perovskite solar cell materials are bringing us closer to this dream with record solar-energy-to-electricity conversion efficiencies at an affordable price. However, their widespread commercial application is impeded by their toxicity and lack of stability in moist environments. In LearnSolar, I will develop a machine-learning based materials design approach to find more stable and environmentally friendly perovskite materials. Machine learning enables me to search for promising materials in the materials space of perovskite alloys, that is too vast for human exploration. The newly designed materials will be integrated into solar cells by collaborators. Once the right materials have been discovered, cheap solar cells can be manufactured and deployed anywhere in the world to deliver a sustainable future and equal prospects for wellbeing.
Short titleLEARNSOLAR/Rinke
StatusActive
Effective start/end date01/09/202031/08/2024