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Acceleration Consortium applies artificial intelligence to discovery of advanced materials

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IMAGE: Alán Aspuru-Guzik, director of the Acceleration Consortium, Canada 150 Research Chair in Theoretical Chemistry in the Departments of Chemistry and Computer Science at U of T, and Canada CIFAR AI.
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Credit: Johnny Guatto/University of Toronto
TORONTO, ON - The Acceleration Consortium, a new global collaboration between academia, industry and government, based at the University of Toronto (U of T), will use artificial intelligence (AI) and robotics to accelerate the design and discovery of materials that don t yet exist. These advanced materials will make technologies more affordable and eco-friendlier with applications ranging from renewable energy and consumer electronics to drugs. ....

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New Acceleration Consortium at University of Toronto applies artificial intelligence to discovery of advanced materials

New Acceleration Consortium at University of Toronto applies artificial intelligence to discovery of advanced materials
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April 20, 2021
The University of Toronto has launched the Acceleration Consortium (AC), a new global coalition of academia, industry and government that will use artificial intelligence (AI) and robotics to accelerate the design and discovery of materials that don’t yet exist. These advanced materials will make technologies more affordable and eco-friendly with applications ranging from renewable energy and consumer electronics to drugs.
By leveraging the power of AI, robotics, engineering and chemistry, the AC will make U of T a global centre for materials science innovation. Using materials acceleration platforms (MAPs), also known as self-driving laboratories, the AC will rapidly design and discover the materials needed to build a more sustainable, prosperous and healthy future. The AC is led by Professor Alán Aspuru-Guzik with support fr ....

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Chemistry and computer science join forces to apply artificial intelligence to chemical reactions

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Chemistry and computer science join forces to apply artificial intelligence to chemical reactions
In the past few years, researchers have turned increasingly to data science techniques to aid problem-solving in organic synthesis.
Researchers in the lab of Abigail Doyle, Princeton’s A. Barton Hepburn Professor of Chemistry, have developed open-source software that provides them with a state-of-the-art optimization algorithm to use in everyday work, folding what’s been learned in the machine learning field into synthetic chemistry.
Princeton chemists Benjamin Shields and Abigail Doyle worked with computer scientist Ryan Adams (not pictured) to create machine learning software that can optimize reactions – using artificial intelligence to speed through thousands of reactions that chemists used to have to labor through one by one. ....

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