Literature DB >> 29347119

Disentangling structural information from core-level excitation spectra.

Johannes Niskanen1, Christoph J Sahle2, Keith Gilmore2, Frank Uhlig3, Jens Smiatek3, Alexander Föhlisch1,4.   

Abstract

Core-level spectra of liquids can be difficult to interpret due to the presence of a range of local environments. We present computational methods for investigating core-level spectra based on the idea that both local structural parameters and the x-ray spectra behave as functions of the local atomic configuration around the absorbing site. We identify correlations between structural parameters and spectral intensities in defined regions of interest, using the oxygen K-edge excitation spectrum of liquid water as a test case. Our results show that this kind of analysis can find the main structure-spectral relationships of ice, liquid water, and supercritical water.

Entities:  

Year:  2017        PMID: 29347119     DOI: 10.1103/PhysRevE.96.013319

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  2 in total

1.  Physically inspired deep learning of molecular excitations and photoemission spectra.

Authors:  Julia Westermayr; Reinhard J Maurer
Journal:  Chem Sci       Date:  2021-06-30       Impact factor: 9.969

2.  Emulator-based decomposition for structural sensitivity of core-level spectra.

Authors:  J Niskanen; A Vladyka; J Niemi; C J Sahle
Journal:  R Soc Open Sci       Date:  2022-06-08       Impact factor: 3.653

  2 in total

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