Predicting electronic screening for fast Koopmans spectral functional calculations
Koopmans spectral functionals are a powerful extension of Kohn-Sham density-functional
theory (DFT) that enables the prediction of spectral properties with state-of-the-art accuracy …
theory (DFT) that enables the prediction of spectral properties with state-of-the-art accuracy …
Machine Learning for Chemical Looping: Recent Advances and Prospects
Chemical looping is a revolutionary energy conversion method aimed at the low-carbon
transformation of fossil fuels. The development of this technology primarily involves the …
transformation of fossil fuels. The development of this technology primarily involves the …
Magnons from time-dependent density-functional perturbation theory and the noncollinear Hubbard formulation
Spin excitations play a fundamental role in understanding magnetic properties of materials,
and have significant technological implications for magnonic devices. However, accurately …
and have significant technological implications for magnonic devices. However, accurately …
Machine Learning Model for the Prediction of Hubbard U Parameters and Its Application to Fe–O Systems
W Xia, G Chen, Y Zhu, Z Hou, T Tsuchiya… - Journal of Chemical …, 2024 - ACS Publications
Without incurring additional computational cost, the Hubbard model can prevalently address
the electron self-interaction problems of the local or semilocal exchange–correlation …
the electron self-interaction problems of the local or semilocal exchange–correlation …
The Interplay Between Electron Localization, Magnetic Order, and Jahn-Teller Distortion that Dictates LiMnO Phase Stability
The development of Mn-rich cathodes for Li-ion batteries promises to alleviate supply chain
bottlenecks in battery manufacturing. Challenges in Mn-rich cathodes arise from Jahn-Teller …
bottlenecks in battery manufacturing. Challenges in Mn-rich cathodes arise from Jahn-Teller …