Dynamic and membrane DAC ramp dataset storage, raw and azimuthal integrated as xy.files.

The dataset is part of a project exploring the onset of phase transitions, the development of microstrain and the lattice parameters during fast compression rates, resembling those during e.g. propagation seismic shockwaves and large body impacts. The strain rate conditions achieved in our experiments are between those reached in the common static (DAC) and shock experiments. The current dataset contains a selected set of xy.files of azimuthal integrated 2D-diffraction images of an Mg0.2Fe0.8O sample. Diffraction images were collected at ambient temperature (in 2019) at the ECB P02.2 Beamline, PETRA III, DESY, Germany using the piezo-driven dynamic diamond anvil cells (dDAC) in combination with fast LAMBDA GaAs 2M detectors at 25.6 keV (0.4843 Å). The dataset is provided as a test dataset for machine learning application on spectra classification. The version will be updated once the whole work has been published and the full datasets can be made available. Please find below the link towards the machine learning application. https://github.com/European-XFEL-examples/panosc-ml-spectra-classification

本数据集隶属于一项探究快速压缩条件下相变起始、微应变演化与晶格参数变化规律的研究项目，此类快速压缩速率类同于地震冲击波传播与大型天体撞击过程中的压缩条件。本实验实现的应变速率区间，介于常规静态金刚石对顶砧（Diamond Anvil Cell，简称DAC）实验与常规冲击实验的应变速率之间。当前数据集包含一组精选的Mg0.2Fe0.8O样品的方位积分二维衍射图像的xy格式文件。该衍射图像于2019年在德国德意志电子同步加速器（DESY）的PETRA III同步辐射装置ECB P02.2光束线采集，采集过程采用环境温度，结合压电驱动动态金刚石对顶砧（dynamic diamond anvil cells，简称dDAC）与25.6 keV（波长0.4843 Å）的快速LAMBDA GaAs 2M探测器完成。本数据集作为光谱分类机器学习应用的测试数据集对外提供。待整体研究成果正式发表后，我们将更新数据集版本并开放完整数据集。机器学习应用的相关链接如下：https://github.com/European-XFEL-examples/panosc-ml-spectra-classification