five

The solvation shell probed by resonant intermolecular Coulombic decay - data

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://zenodo.org/record/12807453
下载链接
链接失效反馈
官方服务:
资源简介:
Dataset pertaining to the article "The solvation shell probed by resonant intermolecular Coulombic decay", accepted for publication in Nature Communications. Here, we show how a resonant variant of intermolecular Coulombic decay can be used to selectively infer information on the electronic structure of solvent shell molecules around a metal ion in aqueous solution. Experiments were done using a liquid microjet. Files with extension .nxs are hdf5-files structured according to the NeXus standard v2022.07, seehttps://www.nexusformat.org/https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.htmlNeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:* nexpy (distributed with python)* https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium) In each NeXus file-entry, two types of spectra are shown:1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data').2. As-measured data ('raw'). Files with extension .txt are tab-separated ascii-files. Files with exension .zip are zipped archives of several .txt-files. The following files are provided: Photoemission data pertaining to all figures in the article's main text and supplementary information, including all relevant metadata:CaICD_dataset.nxs Numeric representations of the traces shown in the article's and supplementary information's figures, one zipped archive per figure:FigN.zip Version history1: initial upload Contact persons for questions regarding this data set: Rémi Dupuy, remi.dupuy@sorbonne-universite.fr; Uwe Hergenhahn, uhe@fhi.mpg.de. If you use these data for your scientific work we are curious to learn about it.
创建时间:
2024-07-25
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作