Two new papers about GW and BSE@GW method development published in JCTC

We just published a paper about “Benchmark of GW Methods for Core-Level Binding Energies” https://pubs.acs.org/doi/10.1021/acs.jctc.2c00617 and another one about “Combining Renormalized Singles GW Methods with the Betheā€“Salpeter Equation for Accurate Neutral Excitation Energies” https://pubs.acs.org/doi/10.1021/acs.jctc.2c00686 with our collaborators from Duke University (USA).

Our XPS prediction model combining DFT+GW+ML is now out in Chemistry of Materials

Check out our paper at https://pubs.acs.org/doi/10.1021/acs.chemmater.1c04279. For the brave, try our XPS prediction server at http://nanocarbon.fi/xps to obtain a prediction of carbon-based materials within seconds. A short story is also available here: https://miguelcaro.org/wp/2022/07/13/automated-x-ray-photoelectron-spectroscopy-xps-prediction-for-carbon-based-materials-combining-dft-gw-and-machine-learning/

ML predictions of core-level binding energies of carbon-based materials

Check out our latest work on machine learning models for computational predictions of core-electron binding energies of carbon-based materials: Accurate computational prediction of core-electron binding energies in carbon-based materials: A machine-learning model combining DFT and GW (arXiv:2112.06551)