Time-dependent density functional theory calculations of near-edge X-ray absorption fine structure with short-range corrected functionals

文献信息

发布日期 2009-09-25
DOI 10.1039/B912718F
影响因子 3.676
作者

Nicholas A. Besley, Michael J. G. Peach, David J. Tozer


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摘要

We report calculations of core excitation energies and near-edge X-ray absorption fine structure (NEXAFS) spectra computed with time-dependent density functional theory (TDDFT). TDDFT with generalized gradient approximation and standard hybrid exchange–correlation functionals is known to underestimate core excitation energies. This failure is shown to be associated with the self-interaction error at short interelectronic distances. Short-range corrected hybrid functionals are shown to reduce the error in the computed core excitation energies for first and second row nuclei in a range of molecules to a level approaching that observed in more traditional excited states calculations in the ultraviolet region. NEXAFS spectra computed with the new functionals agree well with experiment and the pre-edge features in the NEXAFS spectra of plastocyanin are correctly predicted.

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来源期刊

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
自引率: 10.3%
年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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