AI-Assisted Decision Support Tools to Accelerate Catalytic Materials Design/Discovery: Towards Net-Zero Emissions

This project aims to accelerate the discovery of efficient high-entropy alloy (HEA) catalytic materials for CO2 electrolysis by integrating advanced quantum AI-based optimization techniques with quantum mechanics computation. By combining these cutting-edge methods, the project seeks to identify novel, efficient, and costeffective catalysts that can convert CO2 into valuable products, contributing to the achievement of net-zero emissions.
The participating institutions, including Polytechnique Montréal, CanmetENERGY, and Eindhoven University of Technology, will benefit from enhanced collaboration in advanced materials research, the development of state-ofthe-art data-driven models, and a deeper understanding of electrolysis processes for sustainable energy applications.

Faculty Supervisor:

Ahmed Ragab;Soumaya Yacout

Student:

Partner:

Eindhoven University of Technology

Discipline:

Engineering

Sector:

Education

University:

Polytechnique Montréal

Program: