Materials Horizons Blog

Parastoo Agharezaei is a researcher in the field of materials science and engineering, holding a Bachelor’s degree from the University of Tehran, awarded in 2017. She pursued a Joint Master’s degree with an Erasmus Mundus excellence full scholarship, earning dual Master’s degrees in Materials Science from TU Darmstadt, Germany, and in Physics with a minor in Quantum Modeling of Nanomaterials from the University of Liege, Belgium, in 2020. Currently, Parastoo is advancing her expertise in Computational Materials Science through a Ph.D. program at INRS, University of Quebec, focusing her doctoral thesis on the design of alloy catalysts for ammonia production using Density Functional Theory and Machine Learning.

Title of presentation: Design of CuNi-based single-doped alloy catalysts for ammonia production via Density Functional Theory

Mehdi Shamekhi is currently a PhD candidate in the Department of
Physics at Concordia University, working under the supervision of Prof.
Gilles H. Peslherbe on the computational design and investigation of bimetallic
alloys for the electrocatalytic nitrogen reduction reaction (NRR). Mehdi employs a combination of machine
learning and computational chemistry to advance his research, using
machine learning algorithms to screen the chemical space of bimetallic alloy
catalysts and identify promising candidates for further characterization
via density functional theory. Detailed knowledge of the electronic structure
of these catalysts indeed enables the design of catalysts that are both
active and selective toward the NRR, contributing to the development of efficient
catalysts for sustainable ammonia synthesis. Mehdi aspires to continue
his research in computational chemistry and electrocatalysis, aiming to make
significant contributions to the field of sustainable energy solutions. His longterm
goal is to develop innovative materials that can address global energy
challenges through green chemistry and advanced computational methods.

Title of presentation: Machine learning assisted screening and DFT characterization of bimetallic alloy catalysts for the nitrogen reduction reaction

Yasser Salah Eddine Bouchareb is currently pursuing a Ph.D. program at INRS, University of Quebec, working under the supervision of Prof. Kulbir Ghuman, and co-supervised by Prof. Jonathan Shock, on the design of alloy catalysts for CO2 PhotoCapture using Density Functional Theory and Machine Learning.

Title of presentation: Screening binary alloys for CO2 photo capture using GNN