Data selection strategies for minimizing measurement time in materials characterization
Abstract 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...
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-96221-1 |
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| author | Alexander Liehr Kristina Dingel Daniel Kottke Sebastian Degener David Meier Bernhard Sick Thomas Niendorf |
| author_facet | Alexander Liehr Kristina Dingel Daniel Kottke Sebastian Degener David Meier Bernhard Sick Thomas Niendorf |
| author_sort | Alexander Liehr |
| collection | DOAJ |
| description | Abstract 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. The present study highlights that specific selection strategies, taking into account the prevailing microstructure of the alloy in focus, can decrease counting times in X-ray energy dispersive diffraction experiments without any detrimental effect on data quality for the subsequent analysis. 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 in large-scale facilities. |
| format | Article |
| id | doaj-art-b0502d8e39344ecba0126f1acb6dd6e3 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-b0502d8e39344ecba0126f1acb6dd6e32025-08-20T02:55:29ZengNature PortfolioScientific Reports2045-23222025-04-0115111210.1038/s41598-025-96221-1Data selection strategies for minimizing measurement time in materials characterizationAlexander Liehr0Kristina Dingel1Daniel Kottke2Sebastian Degener3David Meier4Bernhard Sick5Thomas Niendorf6Institute of Materials Engineering, University of KasselIntelligent Embedded Systems, University of KasselIntelligent Embedded Systems, University of KasselBundesanstalt für Materialforschung und -prüfungIntelligent Embedded Systems, University of KasselIntelligent Embedded Systems, University of KasselInstitute of Materials Engineering, University of KasselAbstract 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. The present study highlights that specific selection strategies, taking into account the prevailing microstructure of the alloy in focus, can decrease counting times in X-ray energy dispersive diffraction experiments without any detrimental effect on data quality for the subsequent analysis. 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 in large-scale facilities.https://doi.org/10.1038/s41598-025-96221-1 |
| spellingShingle | Alexander Liehr Kristina Dingel Daniel Kottke Sebastian Degener David Meier Bernhard Sick Thomas Niendorf Data selection strategies for minimizing measurement time in materials characterization Scientific Reports |
| title | Data selection strategies for minimizing measurement time in materials characterization |
| title_full | Data selection strategies for minimizing measurement time in materials characterization |
| title_fullStr | Data selection strategies for minimizing measurement time in materials characterization |
| title_full_unstemmed | Data selection strategies for minimizing measurement time in materials characterization |
| title_short | Data selection strategies for minimizing measurement time in materials characterization |
| title_sort | data selection strategies for minimizing measurement time in materials characterization |
| url | https://doi.org/10.1038/s41598-025-96221-1 |
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