Electronic structure and spectra of (Cu2O)n–H2O complexes

文献信息

发布日期 2014-11-07
DOI 10.1039/C4CP04303K
影响因子 3.676
作者

Jerry Whitten


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摘要

Density functional theory calculations have been employed to determine optimized geometries for different (Cu2O)n clusters for n = 1 to 6, 12 and 18. The results show the formation of (Cu2O)n rings for n ≥ 2, while (Cu2O)n nanobarrels have been determined for n = 12 and for n = 18. Adsorption of H2O on the (Cu2O)n clusters occurs preferentially by interaction of the water O with outer Cu atoms. Absorption spectra calculated by time dependent density functional theory show that in all cases charge-transfer excitations from occupied orbitals of the (Cu2O)n cluster to a Rydberg orbital of H2O contribute to the character of the singlet excited states calculated at energies starting at about 2.6 eV, with increasing contribution found at higher excitation energies. Configuration interaction calculations on selected (Cu2O)n–H2O complexes determine charge-transfer excitations to contribute significantly to excited states lying at 4.6–6.2 eV above the ground state.

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DOI: 10.1039/D0CP90102D

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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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