Machine learning methods move self-driving labs closer to materials discovery at scale

Machine learning doesn't replace human intelligence, but it can outlast human endurance, which makes it a helpful tool for ...
EurekAlert!

Revolutionary machine-learning approach redefines high-temperature alloy design with exceptional strength and ductility

(a) The workflow contains three parts: ML model selection to calculate the expected improvement (EI) values of the target properties for a given alloy; the non-dominated sorting genetic algorithm ...
Phys.org

Machine learning framework accelerates theoretical design of nonlinear optical materials

A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has made strides in the theoretical design of nonlinear optical (NLO) materials by ...
Science Daily

Novel machine learning model can predict material failure before it happens

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...
Semiconductor Engineering

Machine Learning Tools Help Bridge Design-To-Manufacturing Gap

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...