2 citations · 3 across the 5 of their papers we have counts for
5 papers
Predictive autoencoder-transformer model of Cu oxidation state from EELS and XAS spectra
Brian Lee, Linna Qiao, Samuel Gleason +5
X-ray absorption spectroscopy (XAS) and electron energy-loss spectroscopy (EELS) produce detailed information about oxidation state, bonding, and coordination, making them essentia…
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…
Random Forest Prediction of Crystal Structure from Electron Diffraction Patterns Incorporating Multiple Scattering
Samuel P. Gleason, Alexander Rakowski, Stephanie M. Ribet +5
Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new materi…
Prediction of the Cu Oxidation State from EELS and XAS Spectra Using Supervised Machine Learning
Samuel P. Gleason, Deyu Lu, Jim Ciston
Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about bonding, distributions and locations of atoms, and their coordin…
Extracting Structured Seed-Mediated Gold Nanorod Growth Procedures from Literature with GPT-3
Nicholas Walker, John Dagdelen, Kevin Cruse +7
Although gold nanorods have been the subject of much research, the pathways for controlling their shape and thereby their optical properties remain largely heuristically understood…