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Generation, Accumulation, and Utilization of Data in the Automatically Controlled End-Station of a Soft X-ray Beamline — arXiv:2610.11476

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.11476
License (as archived): CC0-1.0
Archived: 2026-10-09T06:39:41.322Z
SHA-256 of the archived text: 5848d506c4e5f94ccf865f838df9a20ff1064c1a04639a53825be20a3ed298fa
Stable URL of this page: https://metraipolis.com/documento/dc_45cd089fbc90

How to cite

Generation, Accumulation, and Utilization of Data in the Automatically Controlled End-Station of a Soft X-ray Beamline — arXiv:2610.11476 — arXiv (en), https://arxiv.org/abs/2610.11476 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_45cd089fbc90 (Metraipolis archive dc_45cd089fbc90, sha256 5848d506c4e5f94ccf865f838df9a20ff1064c1a04639a53825be20a3ed298fa)

BibTeX

@misc{dc45cd089fbc90,
  title = {Generation, Accumulation, and Utilization of Data in the Automatically Controlled End-Station of a Soft X-ray Beamline — arXiv:2610.11476},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.11476},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_45cd089fbc90; sha256 5848d506c4e5f94ccf865f838df9a20ff1064c1a04639a53825be20a3ed298fa},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.11476. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

AI is rapidly transforming materials exploration, yet reliable AI-assisted research depends on experimental data that retains their context, provenance, and machine-readable structure. High-throughput synchrotron measurements therefore require more than automated data acquisition: data generation, accumulation, and utilization must be connected within a continuous workflow. Here, we present a data-centric research framework that integrates the PIONEER system, the OMNES, and ML analysis. The PIONEER system automates sample handling, vacuum transfer, and scanning XAS at the BL08U soft X-ray beamline of NanoTerasu, systematically generating large volumes of spatially resolved spectral data. Measurement and analysis files are stored in the cloud-based ARIM-mdx data system, while OMNES manages metadata describing samples, preparation procedures, measurement conditions, instrument settings, data locations, and analysis histories. Tabular and JavaScript Object Notation formats are used according to the metadata structure, with numerical values stored separately from units to facilitate machine processing. OMNES organizes these records based on causal relationships among experimental and analytical processes, linking samples, measurements, raw data, processed data, and analysis results through a relational data model and visualizing their relationships as a graph. This causality-based organization preserves experimental and analytical provenance and clarifies how each result was derived from the preceding processes and data. The accumulated spectra can subsequently be processed using ML methods, including dimensionality reduction and materials classification, and the resulting data can be registered back into OMNES. Previously reported ML analysis of BN XAS spectra is presented as an example of the analytical workflow that can be applied to data acquired at the beamline.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv physics.data-an, nuovi lavori del giorno).
Categorie arXiv: Materials Science (cond-mat.mtrl-sci) ; Data Analysis, Statistics and Probability (physics.data-an); Instrumentation and Detectors (physics.ins-det).
Pagina del lavoro: https://arxiv.org/abs/2610.11476 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-09T05:59:46.495Z dalla pagina https://arxiv.org/list/physics.data-an/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).