U of T ‘self-driving lab’ to focus on next-gen human tissue models
The Self-Driving Laboratory for Human Organ Mimicry is one of six self-driving labs launched by the Acceleration Consortium to drive research across a range of fields
Tag: Acceleration Consortium
This machine learning method aims to speed up the design of next-generation biomedical implants and aerospace materials
A team led by Professor Yu Zou (MSE) is using a deep learning and genetic algorithm framework to achieve application-specific mechanical properties by microstructure optimization
‘Self-driving labs’: $200-million federal grant powers AI-driven materials discovery for clean energy, advanced manufacturing and more
Funding will enhance the work of the Acceleration Consortium, a multidisciplinary collaboration that includes several U of T Engineering researchers
Exploring ‘chemical space’ with Professor Anatole von Lilienfeld
Lilienfeld (Chemistry, MSE) is using artificial intelligence to discover the potential of undiscovered chemical combinations
Acceleration Consortium at U of T welcomes Anatole von Lilienfeld as inaugural Clark chair in advanced materials discovery
Professor von Lilienfeld, whose appointment will be shared with the Department of Materials Science & Engineering, will play a key role in developing new materials that do not exist yet
New Acceleration Consortium at University of Toronto applies artificial intelligence to discovery of advanced materials
Global coalition aims to accelerate research of new materials that will increase affordability and sustainability in a wide range of applications