On-the-fly segmentation approaches for x-ray diffraction datasets for metallic glasses
Abstract
Investment in brighter sources and larger detectors has resulted in an explosive rise in the data collected at synchrotron facilities. Currently, human experts extract scientific information from these data, but they cannot keep pace with the rate of data collection. Here, we present three on-the-fly approaches—attribute extraction, nearest-neighbor distance, and cluster analysis—to quickly segment x-ray diffraction (XRD) data into groups with similar XRD profiles. An expert can then analyze representative spectra from each group in detail with much reduced time, but without loss of scientific insights. As a result, on-the-fly segmentation would, therefore, result in accelerated scientific productivity.
- Authors:
-
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Univ. of South Carolina, Columbia, SC (United States)
- National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States)
- Publication Date:
- Research Org.:
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1394638
- Grant/Contract Number:
- AC02-76SF00515
- Resource Type:
- Accepted Manuscript
- Journal Name:
- MRS Communications
- Additional Journal Information:
- Journal Volume: 7; Journal Issue: 03; Journal ID: ISSN 2159-6859
- Publisher:
- Materials Research Society - Cambridge University Press
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE; X-ray diffraction (XRD); amorphous metal
Citation Formats
Ren, Fang, Williams, Travis, Hattrick-Simpers, Jason, and Mehta, Apurva. On-the-fly segmentation approaches for x-ray diffraction datasets for metallic glasses. United States: N. p., 2017.
Web. doi:10.1557/mrc.2017.76.
Ren, Fang, Williams, Travis, Hattrick-Simpers, Jason, & Mehta, Apurva. On-the-fly segmentation approaches for x-ray diffraction datasets for metallic glasses. United States. https://doi.org/10.1557/mrc.2017.76
Ren, Fang, Williams, Travis, Hattrick-Simpers, Jason, and Mehta, Apurva. Wed .
"On-the-fly segmentation approaches for x-ray diffraction datasets for metallic glasses". United States. https://doi.org/10.1557/mrc.2017.76. https://www.osti.gov/servlets/purl/1394638.
@article{osti_1394638,
title = {On-the-fly segmentation approaches for x-ray diffraction datasets for metallic glasses},
author = {Ren, Fang and Williams, Travis and Hattrick-Simpers, Jason and Mehta, Apurva},
abstractNote = {Investment in brighter sources and larger detectors has resulted in an explosive rise in the data collected at synchrotron facilities. Currently, human experts extract scientific information from these data, but they cannot keep pace with the rate of data collection. Here, we present three on-the-fly approaches—attribute extraction, nearest-neighbor distance, and cluster analysis—to quickly segment x-ray diffraction (XRD) data into groups with similar XRD profiles. An expert can then analyze representative spectra from each group in detail with much reduced time, but without loss of scientific insights. As a result, on-the-fly segmentation would, therefore, result in accelerated scientific productivity.},
doi = {10.1557/mrc.2017.76},
journal = {MRS Communications},
number = 03,
volume = 7,
place = {United States},
year = {2017},
month = {8}
}
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