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cond-mat.mtrl-sci2024
CuXASNet: Rapid and Accurate Prediction of Copper L-edge X-Ray Absorption Spectra Using Machine Learning
Samuel P. Gleason, Matthew R. Carbone, Deyu Lu +1
In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu L-edge X-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu lo…
cond-mat.mtrl-sci2024
Tailored topotactic chemistry unlocks heterostructures of magnetic intercalation compounds
Samra Husremović, Oscar Gonzalez, Berit H. Goodge +15
The construction of thin film heterostructures has been a widely successful archetype for fabricating materials with emergent physical properties. This strategy is of particular im…
cond-mat.mtrl-sci2010
Atomic Imaging Using Secondary Electrons in a Scanning Transmission Electron Microscope : Experimental Observations and Possible Mechanisms
H. Inada, D. Su, R. F. Egerton +5
We report our detailed investigation of high-resolution imaging using secondary electrons (SE) with a subnanometer probe in an aberration-corrected transmission electron microscope…