The mechanism of excited-state proton transfer in 1-naphthol–piperidine clusters
文献信息
发布日期
2015-09-04
DOI
10.1039/C5CP03620H
影响因子
3.676
作者
Toshihiko Shimizu, Shun Manita, Shunpei Yoshikawa, Kenro Hashimoto, Mitsuhiko Miyazaki, Masaaki Fujii
查看原文
摘要
The geometries of 1-naphthol–(piperidine)n (1-NpOH–(Pip)n) (n = 0–3) clusters have been calculated by using density functional theory (DFT) and time-dependent density functional theory (TD-DFT) methods to investigate excited-state proton transfer (ESPT) in the low-lying singlet excited states, La and Lb. For the n = 1 cluster, no PT structure was found in Lb and La as well as the ground state, S0. For n = 2, optically accessible Lb from S0 shows the PT structure. We therefore concluded that the threshold size of ESPT is n = 2, which is consistent with previous experimental results. ESPT in 1-NpOH–(Pip)n is simply triggered by optical excitation to Lb. It is essentially different from the 1-NpOH–(NH3)n cluster in which an internal conversion process is required to promote ESPT. From the calculated structures, the importance of the solvation of the π-ring is strongly suggested rather than the proton affinity in ESPT.
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来源期刊
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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