Physics

Electron density

Electron

Core electron

Algorithm

Composite number

Optics

Statistical physics

Density functional theory

Carbon fibers

Computational chemistry

Core (optical fiber)

Chemistry

Materials science

Computer science

Quantum mechanics

Computational physics

Chemistry of Materials

We present a quantitatively accurate machine-learning (ML) model for the computational prediction of core-electron binding energies, from which X-ray photoelectron spectroscopy (XPS) spectra can be readily obtained. Our model combines density functional theory (DFT) with

Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and <i>GW</i>

Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and GW