(Nanowerk News) Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon ...

From left to right: An image of the full lattice geometry is juxtaposed with an 18.75-million cell lattice floating on a bubble. Credit: Peter Serles / University of Toronto Engineering Researchers at ...

Add Yahoo as a preferred source to see more of our stories on Google. Researchers have developed high-performance nano-architected materials that have the strength of carbon steel but the lightness of ...

Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon steel but the ...

What just happened? Researchers at the University of Toronto's Faculty of Applied Science & Engineering have harnessed the power of machine learning to create nanomaterials that combine carbon steel's ...

Artificial intelligence is accelerating the design of microfluidic devices, replacing months of manual iteration with rapid, data-driven optimization. Techniques like Bayesian optimization and machine ...