News — Dounia Shaaban Kabakibo inherited her love of science from her father. Telescope in hand, her dad inspired her to gaze at the stars and planets, learn about the mysteries of physics, and strive to “get to the bottom of things.”
After leaving Syria with him and her mother and sister, Kakakibo spent two years in Saudi Arabia before settling in Quebec, where she quickly mastered French. Her curiosity about how the world works then took her to Université de Montréal, where she completed two degrees.
First was a bachelor’s in mathematics and physics, then she got a master’s in physics. Now she is pursuing a doctorate in condensed matter physics at the Institut Courtois, working with UdeM physics professor Michel Côté.
Condensed matter physics is the study of substances with particles dense enough to interact strongly and form solids, liquids or “exotic” states. These interactions produce unique behaviours not observed in isolated atoms or molecules.
The quest for new materials with novel properties is what drives Kabakibo.
Rethinking batteries
Her research centres on new materials for solid-state batteries. At present, battery electrolytes—the substances that allow ions to circulate—are mainly composed of liquids or gels, making them potentially flammable. Kabakibo is exploring the potential of crystals.
“By crystals we mean a periodic arrangement of atoms in space, like diamonds,” she explained. “These solids could extend the life of batteries and make them safer by reducing the risk of fire. They could also offer better energy density, making it possible to design lighter batteries.”
Such longer-lasting and efficient batteries would have many applications in an increasingly electrified world, particularly in the automotive industry, she said.
“We’re not yet at the stage where these batteries can be produced on an industrial scale – the materials aren’t optimal yet – but I’m optimistic we’ll get there.”
A boost from AI
In addition to her work at the Institut Courtois, Kabakibo is doing a research internship at Mila—Quebec Artificial Intelligence Institute under the supervision of Yoshua Bengio, a star professor in UdeM’s Department of Computer Science and Operations Research.
She is using machine-learning models to rapidly test thousands of atomic combinations and identify those most likely to yield optimal properties.
“It’s so exciting to be at the intersection of machine learning and physics,” Kabakibo said. “I feel this could be the future of scientific research—using all these tools to advance our knowledge.”
RSS