Convolutional neural network framework for the automated analysis of transition 
metal X-ray photoelectron spectra

Pielsticker, Lukas; Nicholls, Rachel L.; DeBeer, Serena; Greiner, Mark

doi:10.1016/j.aca.2023.341433

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Convolutional neural network framework for the automated analysis of transition metal X-ray photoelectron spectra

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Pielsticker, Lukas
Research Department Schlögl, Max Planck Institute for Chemical Energy Conversion, Max Planck Society;

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Nicholls, Rachel L.
Research Department Schlögl, Max Planck Institute for Chemical Energy Conversion, Max Planck Society;

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DeBeer, Serena
Research Department DeBeer, Max Planck Institute for Chemical Energy Conversion, Max Planck Society;

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Greiner, Mark
Research Department Schlögl, Max Planck Institute for Chemical Energy Conversion, Max Planck Society;

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Pielsticker, L., Nicholls, R. L., DeBeer, S., & Greiner, M. (2023). Convolutional neural network framework for the automated analysis of transition metal X-ray photoelectron spectra. Analytica Chimica Acta, (1271): 341433. doi:10.1016/j.aca.2023.341433.

Cite as: https://hdl.handle.net/21.11116/0000-000D-D921-9

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