The company has partnered with BanQu, reportedly the first-ever, patented and largest end-to-end, non-crypto blockchain Supply Chain Sustainability platform, to develop the technology.
Neural Networks Predict Material Structures, Behaviors Faster July 13, 2021 Contact Author Rachel Grabenhofer
Close
Sponsored
Phys.org describes how Mark Messner, an engineer at the U.S. Department of Energy s Argonne National Laboratory, has applied facial recognition technology to aid in materials discovery by predicting structures based on given properties.
Messner initially published his work in 2020 in the
Journal of Mechanical Design, wherein he explains how convolutional neural networks (CNNs) in AI have successfully been applied to categorize images based on raw pixel data. He applied CNNs to periodic microstructures with the goal of identifying a faster model for calculating their effective properties.