Simple accuracy boost for core excitation calculations
![Relativistic corrections (RC) greatly improve the accuracy of evGW0 calculations for the CORE65 benchmark set of molecular core excitations](/sites/g/files/flghsv161/files/styles/o_288w_ah_n/public/2020-10/Relativistic_press_image.png?itok=l0K7xQbC)
Core level spectroscopy is an important experimental technique in physics, chemistry and materials science. Core level experiments are often accompanied by quantum mechanical calculations that aid the interpretation of the measured data. A promising recent development is to use the GW Green's function formalism as the quantum mechanical method of choice, which offers several distinct advantages over the conventional density-functional theory (DFT) choice.
CEST researchers have now derive a relativistic correction scheme that improves the accuracy of 1s core-level binding energies calculated from Green’s function theory in the GW approximation. The scheme is element specific and does not add computational overhead. It reduces the mean absolute error (MAE) of previously reported benchmark set of 65 core-state excitations [D. Golze et al., J. Phys. Chem. Lett. 11, 1840–1847 (2020)] from 0.55 eV to 0.30 eV and eliminates the species dependence of the MAE, which otherwise increases with the atomic number. The correction terms are available in the corresponding publication and can now be widely deployed in molecular and materials science.
More details can be found in the following publication:
Relativistic correction scheme for core-level binding energies from GW, Levi Keller, Volker Blum, Patrick Rinke, and Dorothea Golze, J. Chem. Phys. 153, 114110 (2020)
- Published:
- Updated:
Read more news
![Group Picture](/sites/g/files/flghsv161/files/styles/2_3_288w_125h_d/public/2024-07/Deploy-AI_group_picture_web.jpg?h=9d18ca6b&itok=qW6RB4El)
DeployAI Partners Gather for Heart Beat Meeting in Helsinki
The European DeployAI project's partners gathered for the Heart Beat meeting hosted by Aalto University Executive Education in Helsinki.![Professori Maria Sammalkorpi](/sites/g/files/flghsv161/files/styles/2_3_288w_125h_d/public/2024-07/Aalto_University_Maria_Sammalkorpi_10-6-2024_photo_by_Mikko_Raskinen_002.jpg?h=3c516e57&itok=akEFnUgM)
Get to know us: Associate Professor Maria Sammalkorpi
Sammalkorpi received her doctorate from Helsinki University of Technology 2004. After her defence, she has worked as a researcher at the Universities of Princeton, Yale and Aalto.![AI applications](/sites/g/files/flghsv161/files/styles/2_3_288w_125h_d/public/2022-11/Ai_applications_illustration_Matti_Ahlgren.png?h=5cf565ba&itok=EjV6w68S)
Aalto computer scientists in ICML 2024
Computer scientists in ICML 2024![Photo: Tima Miroschnichenko, Pexels.](/sites/g/files/flghsv161/files/styles/2_3_288w_125h_d/public/2024-07/pexels-tima-miroshnichenko-5992553-%283%29.jpg?h=2c2d78ee&itok=kOaxt7fM)