Near field plasmonic gradient effects on high vacuum tip-enhanced Raman spectroscopy
文献信息
Mengtao Sun
Near field gradient effects in high vacuum tip-enhanced Raman spectroscopy (HV-TERS) are a recent developing ultra-sensitive optical and spectral analysis technology on the nanoscale, based on the plasmons and plasmonic gradient enhancement in the near field and under high vacuum. HV-TERS can not only be used to detect ultra-sensitive Raman spectra enhanced by surface plasmon, but also to detect clear molecular IR-active modes enhanced by strongly plasmonic gradient. Furthermore, the molecular overtone modes and combinational modes can also be experimentally measured, where the Fermi resonance and Darling–Dennison resonance were successfully observed in HV-TERS. Theoretical calculations using electromagnetic field theory firmly supported experimental observation. The intensity ratio of the plasmon gradient term over the linear plasmon term can reach values greater than 1. Theoretical calculations also revealed that with the increase in gap distance between tip and substrate, the decrease in the plasmon gradient was more significant than the decrease in plasmon intensity, which is the reason that the gradient Raman can be only observed in the near field. Recent experimental results of near field gradient effects on HV-TERS were summarized, following the section of the theoretical analysis.
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来源期刊
Physical Chemistry Chemical Physics

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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