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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.

Mark messnerArgonne national laboratoryMechanical designSurvey predictsEmerging techReceive mostஆர்கோன் தேசிய ஆய்வகம்இயந்திர வடிவமைப்புவளர்ந்து வருகிறது தொழில்நுட்பம்