Convolutional neural network framework for the automated analysis of transition metal X-ray photoelectron spectra
Author:
Funder
Max-Planck-Gesellschaft
Publisher
Elsevier BV
Subject
Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry
Reference52 articles.
1. Practical guide for curve fitting in X-ray photoelectron spectroscopy;Major;J. Vac. Sci. Technol. A: Vac. Surf. Films,2020
2. The use and misuse of curve fitting in the analysis of core X-ray photoelectron spectroscopic data;Sherwood;Surf. Interface Anal.,2019
3. A discussion of approaches for fitting asymmetric signals in X-ray photoelectron spectroscopy (XPS), noting the importance of Voigt-like peak shapes;Major;Surf. Interface Anal.,2021
4. X-ray photoelectron spectroscopy: towards reliable binding energy referencing;Greczynski;Prog. Mater. Sci.,2020
5. Assessment of the frequency and nature of erroneous X-ray photoelectron spectroscopy analyses in the scientific literature;Major;J. Vac. Sci. Technol. A: Vac. Surf. Films,2020
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