39 citations · 233 across the 27 of their papers we have counts for
3 papers · 1 filter
Structural Descriptors and Information Extraction from X-ray Emission Spectra: Aqueous Sulfuric Acid
E. A. Eronen, A. Vladyka, Ch. J. Sahle +1
Machine learning can reveal new insights into X-ray spectroscopy of liquids when the local atomistic environment is presented to the model in a suitable way. Many unique structural…
Emulator-based Decomposition for Structural Sensitivity of Core-level Spectra
Johannes Niskanen, Anton Vladyka, Joonas Niemi +1
We explore the sensitivity of several core-level spectroscopic methods to the underlying atomistic structure by using the water molecule as our test system. We first define a metri…
Machine learning in interpretation of electronic core-level spectra
Johannes Niskanen, Anton Vladyka, J. Antti Kettunen +1
Electronic transitions involving core-level orbitals offer a localized, atomic-site and element specific peek window into statistical systems such as molecular liquids. Although fo…