Nature

An active machine learning approach for optimal design of magnesium alloys using Bayesian optimisation

In the pursuit of magnesium (Mg) alloys with targeted mechanical properties, a multi-objective Bayesian optimisation workflow is presented to enable optimal Mg-alloy design. A probabilistic Gaussian ...
Nature

Bayesian-optimization-assisted discovery of stereoselective aluminum complexes for ring-opening polymerization of racemic lactide

The alternative text for this image may have been generated using AI. Fig. 2: Benchmarking the machine learning algorithms. The alternative text for this image may have been generated using AI. Fig. 3 ...
Nanowerk

Strong as steel, light as foam: Machine learning and nano-3D printing create breakthrough nano-architected materials

(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 ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
Phys.org

Machine learning and 3D printing yield steel-strong, foam-light materials

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 ...
EurekAlert!

Strong as steel, light as foam: Machine learning and nano-3D printing produce breakthrough high-performance, nano-architected materials

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 ...