Machine Learning on Experimental Data for Optimizing Colloidal Quantum Dot Solar Cells
Program:
Electrical and Computer Engineering
Project Description:
In this project, we used machine learning models to assist in the characterization process of PbS colloidal quantum dot (CQD) solar cells. We performed spatially-resolved optoelectronic measurements and used experimental data to train a neural network to automatically predict several materials parameters.
Team Members
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Project Mentors, Sponsors, and Partners
Susanna Thon
Course Faculty
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