FURI | Spring 2024

Identifying Defects in Perovskite Using Machine Vision

Energy icon, disabled. An orange lightning bolt.

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