Suppr超能文献

通过拉曼光谱和电导研究相结合来确定单分子结的分子吸附位点。

Identifying the molecular adsorption site of a single molecule junction through combined Raman and conductance studies.

作者信息

Kaneko Satoshi, Montes Enrique, Suzuki Sho, Fujii Shintaro, Nishino Tomoaki, Tsukagoshi Kazuhito, Ikeda Katsuyoshi, Kano Hideaki, Nakamura Hisao, Vázquez Héctor, Kiguchi Manabu

机构信息

Department of Chemistry , School of Science , Tokyo Institute of Technology , 2-12-1 W4-10 Ookayama , Meguro-ku , Tokyo 152-8551 , Japan . Email:

Institute of Physics , Academy of Sciences of the Czech Republic , Cukrovarnicka 10 , Prague CZ-162 00 , Czech Republic . Email:

出版信息

Chem Sci. 2019 Jun 5;10(25):6261-6269. doi: 10.1039/c9sc00701f. eCollection 2019 Jul 7.

Abstract

Single-molecule junctions are ideal test beds for investigating the fundamentals of charge transport at the nanoscale. Conducting properties are strongly dependent on the metal-molecule interface geometry, which, however, is very poorly characterized due to numerous experimental challenges. We report on a new methodology for characterizing the adsorption site of single-molecule junctions through the combination of surface enhanced Raman scattering (SERS), current-voltage (-) curve measurements, and density functional theory simulations. This new methodology discriminates between three different adsorption sites for benzenedithiol and aminobenzenethiol junctions, which cannot be identified by solo measurements of either SERS or - curves. Using this methodology, we determine the interface geometry of these two prototypical molecules at the junction and its time evolution. By modulating the applied voltage, we can change and monitor the distribution of adsorption sites at the junction.

摘要

单分子结是研究纳米尺度电荷传输基本原理的理想试验平台。导电特性强烈依赖于金属 - 分子界面几何结构,然而,由于众多实验挑战,该结构的特征描述非常不完善。我们报告了一种通过结合表面增强拉曼散射(SERS)、电流 - 电压(I - V)曲线测量和密度泛函理论模拟来表征单分子结吸附位点的新方法。这种新方法区分了苯二硫醇和氨基苯硫醇结的三种不同吸附位点,这是单独的SERS或I - V曲线测量无法识别的。使用这种方法,我们确定了这两种典型分子在结处的界面几何结构及其时间演变。通过调节施加电压,我们可以改变并监测结处吸附位点的分布。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4e7/6615215/dd69e94b518f/c9sc00701f-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验