Automated end-station at the soft X-ray beamline featuring robotic air-to-ultrahigh-vacuum sample transfer, scanning probe spectroscopy, and machine learning analysis
Abstract
Driven by the growing integration of artificial intelligence and robotics in experimental science, we redefine the execution of user experiments at synchrotron soft X-ray beamlines by developing a highly automated end-station that can be operated without on-site staff. Installed at beamline BL08U of NanoTerasu, the system comprises four chamber units and two robots that automatically transfer samples from ambient air to an ultrahigh vacuum measurement stage for spectroscopic evaluations, before returning them to their original locations post-measurement. Soft X-ray absorption spectra are automatically acquired once programmed by scanning the micro-focused beam over the designated sample area, followed by automated evaluation using machine learning techniques such as principal-component analysis, multidimensional scaling, t-distributed stochastic neighbour embedding, and uniform manifold approximation and projection. The high-throughput data are systematically accumulated in the database for remote user examination. This unstaffed end-station provides efficient beamtime for users and allows beamline scientists/technicians to pursue more human and creative endeavors.
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BibTeX
@misc{hiromori2026automated,
title = {{Automated end-station at the soft X-ray beamline featuring robotic air-to-ultrahigh-vacuum sample transfer, scanning probe spectroscopy, and machine learning analysis}},
author = {Keita Hiromori and Masashige Miyamoto and Masafumi Horio and Takeru Nakashima and Yasunobu Ando and Masato Kotsugi and Iwao Matsuda},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.22384},
eprint = {2610.22384},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.22384},
}
RIS
TY - UNPB
TI - Automated end-station at the soft X-ray beamline featuring robotic air-to-ultrahigh-vacuum sample transfer, scanning probe spectroscopy, and machine learning analysis
AU - Keita Hiromori
AU - Masashige Miyamoto
AU - Masafumi Horio
AU - Takeru Nakashima
AU - Yasunobu Ando
AU - Masato Kotsugi
AU - Iwao Matsuda
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2610.22384
UR - https://arxiv.org/abs/2610.22384
AB - Driven by the growing integration of artificial intelligence and robotics in experimental science, we redefine the execution of user experiments at synchrotron soft X-ray beamlines by developing a highly automated end-station that can be operated without on-site staff. Installed at beamline BL08U of NanoTerasu, the system comprises four chamber units and two robots that automatically transfer samples from ambient air to an ultrahigh vacuum measurement stage for spectroscopic evaluations, before returning them to their original locations post-measurement. Soft X-ray absorption spectra are automatically acquired once programmed by scanning the micro-focused beam over the designated sample area, followed by automated evaluation using machine learning techniques such as principal-component analysis, multidimensional scaling, t-distributed stochastic neighbour embedding, and uniform manifold approximation and projection. The high-throughput data are systematically accumulated in the database for remote user examination. This unstaffed end-station provides efficient beamtime for users and allows beamline scientists/technicians to pursue more human and creative endeavors.
ER -