The Acceleration Consortium brings together partners from academia, government and industry who are accelerating the discovery of materials and molecules needed for a sustainable future. PHOTO courtesy Acceleration Consortium.
The University of Toronto has been awarded a $200-million grant from the Canada First Research Excellence Fund (CFREF) to revolutionize the speed and impact of scientific discovery through its Acceleration Consortium, reports the U of T Engineering News.
The funding – the largest federal research grant ever awarded to a Canadian university – will support the consortium’s work on ‘self-driving labs’ that combine artificial intelligence, robotics and advanced computing to discover new materials and molecules for a variety of industries, including additive manufacturing, in a fraction of the usual time and cost.
“The University of Toronto is grateful for this significant investment in artificial intelligence-driven research and innovation, which promises to improve the lives of Canadians and those of people around the world,” U of T President Meric Gertler toldU of T Engineering News. “The federal government’s critical support of this initiative builds on years of strategic planning and decisions in this space by the University and the federal government, including the 2017 launch of the Pan-Canadian Artificial Intelligence Strategy that helped cement Toronto’s status as a global hub for a revolutionary technology.
Launched as an Institutional Strategic Initiative in 2021, the Acceleration Consortium brings together partners from academia, government and industry who are accelerating the discovery of materials and molecules needed for a sustainable future. The consortium aims to reduce the time and cost of bringing advanced materials to market, from an average of 20 years and $100 million to as little as one year and $1 million.
The multidisciplinary, collaborative team that makes up the Acceleration Consortium includes several U of T Engineering researchers working at the leading edge of new materials discovery. Examples include:
- Professor Jason Hattrick-Simpers (MSE) — Hattrick-Simpers and his team are in the process of building a new device they’ve named the ‘Sputtertron.’ The system will not only be capable of creating new alloys via a chemical deposition process known as sputtering, but it will also be able autonomously characterize and analyze the electronic properties of those new alloys. Those properties will then be used by the model to imagine the next material to be made, and direct its creation, all without any human intervention — the approach is an example of a ‘self-driving lab.’
- Professor Yu Zou (MSE) — Zou leads the University of Toronto’s first metal additive manufacturing laboratory. The technology is similar to 3D printing, except that it focuses on components made of metal rather than plastic. Additive manufacturing significantly reduces production time, material cost and energy consumption when producing objects. Examples include aerospace engine components, tooling parts for automotive production, critical components for nuclear reactors and joint implants.
- Professor Gisele Azimi (MSE) — Azimi and her team at U of T Engineering’s Laboratory for Strategic Materials have proposed a new, more sustainable method to mine valuable metals from lithium-ion batteries that have reached the end of their useful lifespan. Besides lithium itself, examples of these metals include cobalt, nickel and manganese. The work could enhance both the security and efficiency of supply chains for these critical materials.
- Professor David Sinton (MIE) —Electrochemistry — the use of electricity to drive forward a chemical reaction — can be used to convert captured carbon into valuable products, such as fuels or industrial chemicals. Sinton and his collaborators are developing advanced electrocatalysts that can lower the energy cost of these reactions and increase the economic incentives to capture and recycle carbon.
“Our goal is to accelerate science,” Acceleration Consortium Director Alán Aspuru-Guzik, a professor in the departments of chemistry and computer science told the U of T Engineering News. “To do that, we realized we need to take a cue from self-driving cars and extended that concept to a self-driving lab, which uses AI and automation to carry out more experiments in a smarter way. We’ve essentially supercharged the process of scientific discovery.”
