Practical applications of AI in sustainability

Perovskite solar cells are a specific type of solar cell that has become popular in recent years due to their low making cost and higher ability to produce electricity from sunlight. My research project aims to train a neural network that can help predict different characteristics of a perovskite solar cell, thus helping to increase the amount of electricity it can produce from sunlight. A neural network is a method in artificial intelligence that teaches computers to process data in a way the human brain functions. By using neural networks, we can produce accurate predictions on various characteristics(power conversion efficiency, fill factor, open-circuit voltage, etc.) of a perovskite solar cell by just entering data and graphs. It largely facilitates our research on improving the perovskite solar cell to produce more electricity. By obtaining an improved perovskite solar cell, we can use more solar energy in our lives instead of non-renewable energies, thus obtaining a greener and more sustainable future.

Faculty Supervisor:

Arthur Chan

Student:

Partner:

National University of Singapore

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program: