Machine learning enables predictive modeling of 2-D materials DOE/Argonne National Laboratory

IMAGE: The Argonne research team that has pioneered the use of machine learning tools in 2-D material modeling. view more Credit: Wes Agresta/Argonne National Laboratory Machine learning, a field focused on training computers to recognize patterns in data and make new predictions, is helping doctors more accurately diagnose diseases and stock analysts forecast the rise and fall of financial markets. And now materials scientists have pioneered another important application for machine learning — helping to accelerate the discovery and development of new materials. Researchers at the Center for Nanoscale Materials and the Advanced Photon Source, both U.S. Department of Energy (DOE) Office of Science User Facilities at DOE’s Argonne National Laboratory, announced the use of machine learning tools to accurately predict the physical, chemical and mechanical properties of nanomaterials. In a…


Link to Full Article: Machine learning enables predictive modeling of 2-D materials DOE/Argonne National Laboratory

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