Reflectometry curves (XRR and NR) and corresponding fits for machine learning

This is a compiled dataset of raw X-ray reflectivity (XRR, reflectometry) measurements together with corresponding fit parameters, intentionally published to use as training or test data for machine learning models. (The authors aim to include NR data in further versions of this dataset and plan to include other substrates and materials for XRR. Contributions welcome!) <br> <strong>An interactive documentation can be found in <em>"README.html"</em> or at https://schreiber-lab.github.io/reflectometry-dataset.</strong> Data structure All data is provided in an hdf5 file, following NeXus convention with respect to the provided metadata in the hdf5 attributes. Some datesets have been measured in-situ and therefore there are stacks of curves that correspond to the different layer thicknesses of the same material on top of SiOx. The measured data is provided under experimental and the corresponding fit parameters under fit. Additional information is collected in metadata. Where to find the dataset and how to contribute Have a look at github and zenodo. In case you wish to contribute further curves to this dataset or have ideas how to improve the dataset or where else to deposit it, please contact the authors at softmatter AT ifap.uni-tuebingen.de.本数据集整合了原始X射线反射率（X-ray Reflectivity, XRR，反射计量法）测量数据与对应的拟合参数，专为机器学习模型的训练或测试而发布。（作者计划在该数据集的后续版本中加入中子反射（Neutron Reflectometry, NR）数据，并为XRR数据集拓展更多基底与材料类型，欢迎各界贡献数据！） 交互式文档可参阅README.html或访问网址：https://schreiber-lab.github.io/reflectometry-dataset。 数据结构 所有数据均存储于分层数据格式5（Hierarchical Data Format 5, HDF5）文件中，且其HDF5属性内的元数据遵循NeXus规范。部分数据集为原位测量所得，因此包含多组曲线堆栈，对应同一材料在SiOₓ基底上的不同层厚度。实测数据存储于experimental组下，对应的拟合参数则存储于fit组下，其余补充信息收纳于元数据中。 数据集获取与贡献方式 可通过GitHub与Zenodo获取本数据集。若您希望为数据集贡献更多曲线，或对数据集改进、其他存储平台选择有相关建议，请通过邮箱softmatter AT ifap.uni-tuebingen.de与作者联系。