Automation of next generation photovoltaic measurement capabilities

The proposed research project at the Turak Functional Nanomaterials Research group at Concordia aims to enhance the efficiency of solar energy data measurement and analysis from emerging solar cell technologies. In a world increasingly focused on sustainable energy sources, efficient utilization of solar power is paramount. The lab manages vast data, including complex images of nanoparticle arrays, mapping “dark” spots in active layers, and high-throughput current-voltage data crucial for optimizing solar cells. However, the measurement and analysis methods are time-consuming and often require manual intervention at multiple points in the process.

The primary objective of this project is to simplify and automate these processes. User-friendly graphical interfaces will make data measurement and analysis accessible to all. Additionally, program reliability will be enhanced with a universal control system for efficient management of various tools. The team also plans to explore machine learning techniques to extract design rules for optimal nanoparticle arrays used as interfacial tuning layers, promising a leap in the efficiency and precision of solar cell development. This project is a step toward an era where harnessing solar power is not only efficient but seamlessly integrated into our lives, furthering the global shift toward sustainable energy solutions.

Faculty Supervisor:

Ayse Turak

Student:

Partner:

Institut National des Sciences Appliquées de Rennes

Discipline:

Computer science

Sector:

Biotechnology; Green/Alternative Energy; Information and Communications Technology

University:

Concordia University

Program: