FURI | Spring 2024
Identifying Defects in Perovskite Using Machine Vision
Next-generation technologies such as perovskite solar cells have proven to be the lowest cost of any solar technology if they can be successfully manufactured. However, defects in perovskite can reduce efficiency and manufacturability. This study uses machine vision and traditional methods to discover such defects, which aids in understanding their nature and consequences along with improving fault diagnosis as a future form of quality control. The project aims to calibrate and improve it for detecting defects in various perovskite compositions and form factors. This discovery accelerates the development of defect-free perovskite materials, contributing to sustainable energy solutions.
Student researcher
Sanskar Srivastava
Computer science
Hometown: Lucknow, Uttar Pradesh, India
Graduation date: Fall 2026