Multi-code Benchmark on Ti K-edge X-ray Absorption Spectra of Ti-O Compounds
ORAL
Abstract
X-ray absorption spectroscopy (XAS) is an element-specific characterization technique that is sensitive to a material's structure and electronic properties. First-principles XAS simulations have been widely used as to interpret spectra and draw physical insights. Recently, there has also been a growing interest in building computational XAS databases to enable machine learning applications. While several codes are widely used to calculate XAS, non-trivial differences exist both in their underlying formalism and implementation. A systematic comparison between these codes is crucial for assessing reliability and reproducibility of computational XAS data.
In this work, we benchmark Ti K-edge XAS simulations of Ti-O binary compounds using three state-of-the-art codes: XSPECTRA, OCEAN, and EXCITING. We study their convergence behavior with respect to input parameters and present a workflow to automate and standardize inputs to ensure reliable spectra. This allows us to quantitatively compare the results from the three codes and understand the effects due to differences in their treatment of the electron--core-hole interaction.
In this work, we benchmark Ti K-edge XAS simulations of Ti-O binary compounds using three state-of-the-art codes: XSPECTRA, OCEAN, and EXCITING. We study their convergence behavior with respect to input parameters and present a workflow to automate and standardize inputs to ensure reliable spectra. This allows us to quantitatively compare the results from the three codes and understand the effects due to differences in their treatment of the electron--core-hole interaction.
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Presenters
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John Vinson
National Institute of Standards and Tech
Authors
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John Vinson
National Institute of Standards and Tech
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Fanchen Meng
Brookhaven National Laboratory
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Senser Selcuk
Brookhaven National Laboratory
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Mark S Hybertsen
Brookhaven National Laboratory
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Benedikt Maurer
Humboldt University of Berlin
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Christian W Vorwerk
University of Chicago
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Claudia Draxl
Humboldt University of Berlin
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Xiaohui Qu
Brookhaven National Laboratory
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Deyu Lu
Brookhaven National Laboratory