Data selection strategies for minimizing measurement time in materials characterization, measurement data

Every new material needs to be assessed and qualified for an envisaged application. A steadily increasing number of new alloys, designed to address challenges in terms of reliability and sustainability, poses significant demands on well-known analysis methods in terms of their efficiency, e.g., in X-Ray diffraction analysis. Particularly in laboratory measurements, where the intensities in diffraction experiments tend to be low, a possibility to adapt the exposure time to the prevailing boundary conditions, i.e., the investigated microstructure, is seen to be a very effective approach. The counting time is decisive for, e.g., complex texture, phase, and residual stress measurements. Traditionally, more measurement points and, thus, longer data collection times lead to more accurate information. Here, too short counting times result in poor signal-to-background ratios and dominant signal noise, respectively, rendering subsequent evaluation more difficult or even impossible. Then, it is necessary to repeat experiments with adjusted, usually significantly longer counting time. To prevent redundant measurements, it is state-of-the-art to always consider the entire measurement range, regardless of whether the investigated points are relevant and contribute to the subsequent materials characterization, respectively. Obviously, this kind of approach is extremely time consuming and, eventually, not efficient. All relevant data including the code are carefully assessed and will be the basis for a widely adapted strategy enabling efficient measurements not only in lab environments but also large scale facilities.

This data set consists of the fully measured data from the diffraction experiments as well as the manuscript for data analyzing.

IMPORTANT: In case you use the data please cite our corresponding article: https://doi.org/10.1038/s41598-025-96221-1