Science Daily

Researchers use machine learning to detect defects in additive manufacturing

Researchers have developed a new method for detecting defects in additively manufactured components. Researchers at the University of Illinois Urbana-Champaign have developed a new method for ...
Business Wire

Do Batteries Need Medicine? Argonne Researchers Enhance Battery Performance With Electrolyte Additives and Machine Learning

LEMONT, Ill.--(BUSINESS WIRE)--Batteries, like humans, require medicine to function at their best. In battery technology, this medicine comes in the form of electrolyte additives, which enhance ...
TCT Magazine

How additive manufacturing can realise the promise of AI at production scale

Tyler Bouchard and Tyler Modelski explore the fundamental changes needed to scale industrial artificial intelligence in ...
EurekAlert!

Machine learning advances non targeted detection of environmental pollutants

A new review highlights how machine learning is transforming the way scientists detect and measure organic pollutants in the ...
EurekAlert!

Researchers use machine learning to detect defects in additive manufacturing

Longitudinal (top) and axial (middle) images of X-Ray CT data of parts with 6 internal defects: a spherical clog, a stellated shaped clog, a cone shaped void, a blob shaped void, an elliptical warp of ...