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cond-mat.mtrl-sci2023
Quantifying physical insights cooperatively with exhaustive search for Bayesian spectroscopy of X-ray photoelectron spectra
Hiroyuki Kumazoe, Kazunori Iwamitsu, Masaki Imamura +4
We analyzed the X-ray photoemission spectra (XPS) of carbon 1s states in graphene and oxygen-intercalated graphene grown on SiC(0001) using Bayesian spectroscopy. To realize highly…
cond-mat.mtrl-sci2023
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning
Naoya Mamada, Masaichiro Mizumaki, Ichiro Akai +1
We estimate the spatial distribution of heterogeneous physical parameters involved in the formation of magnetic domain patterns of polycrystalline thin films by using convolutional…