Machine Learning Potential Analysis of Structural Transition in Cu and Ag Nanoparticles: From Icosahedral to Face-Centered Cubic
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DOI: 10.1021/acs.jctc.5c00791
Abstract: A highly accurate high-dimensional neural network potential (HDNNP), trained using more than 180,000 DFT-calculated structures, is used to investigate the structure or realistic Cu–Ag bimetallic particles, as this is the dominant species during the CO2… read more here.
Keywords: structural transition; learning potential; machine learning; transition nanoparticles ... See more keywords