IPSBrain: A Unified Intelligent Data Analysis Platform for Multimodal Experimental Characterization at Advanced Photon Source

Advanced photon sources deliver X-ray with unprecedented brilliance and coherence, facilitating sophisticated multimodal characterization of diverse materials while simultaneously generating data volumes that far exceed the capacity of traditional, expert-driven analytical workflows. This growing gap between data acquisition and interpretation has become a critical bottleneck for timely scientific discovery, which creates a critical need for high-throughput and automated data analysis tools. Recent advances in artificial intelligence (AI) offer a transformative potential to address this challenge, enabling the direct mapping of complex experimental observations into scientific insights. However, existing AI-driven tools are remain largely fragmented and task-specific, limiting their adoption of modern multimodal experiments at the facility scale. Here we present IPSBrain, a unified AI-powered platform that serves as Intelligent Photon Source Brain for automated analysis of multimodal synchrotron experimental data. The platform integrated a series of novel, self-developed machine-learning-based models that enable automated data analysis from multiple experimental techniques, including diffraction, scattering, X-ray absorption, and tomograph. The platform is accessible through an intuitive web interface, which significantly lowers the technical barrier to advanced scientific data interpretation. By enabling end-to-end intelligent workflows from data acquisition to quantitative physical insight, IPSBrain supports high-throughput, reproducible, and scalable analysis aligned with the operational demands of modern synchrotron radiation sources. IPSBrain not only demonstrates a practical and extensible framework for AI-driven synchrotron data analysis but also establishes a transferable paradigm for intelligent data analysis of other large-scale research infrastructures, such as neutron sources and free-electron lasers.

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Publication Details

Journal
The Journal of Physical Chemistry A
Published
2026-05-29
DOI
https://doi.org/10.1021/acs.jpca.6c01154
Primary Topic
Nuclear Physics and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

IPSBrain: A Unified Intelligent Data Analysis Platform for Multimodal Experimental Characterization at Advanced Photon Source

Haodong Yao, Zuoxin Xi, Liyuan Wu, Yuan Qin et al.
The Journal of Physical Chemistry A
Nuclear Physics and Applications
article

IPSBrain: A Unified Intelligent Data Analysis Platform for Multimodal Experimental Characterization at Advanced Photon Source

Haodong Yao, Zuoxin Xi, Liyuan Wu, Yuan Qin, Y W Sun, Xiangwen Deng, Lin Li, Yihe Pang, Jing Li, Mengdan Han, Lina Zhao
article en

Abstract

Advanced photon sources deliver X-ray with unprecedented brilliance and coherence, facilitating sophisticated multimodal characterization of diverse materials while simultaneously generating data volumes that far exceed the capacity of traditional, expert-driven analytical workflows. This growing gap between data acquisition and interpretation has become a critical bottleneck for timely scientific discovery, which creates a critical need for high-throughput and automated data analysis tools. Recent advances in artificial intelligence (AI) offer a transformative potential to address this challenge, enabling the direct mapping of complex experimental observations into scientific insights. However, existing AI-driven tools are remain largely fragmented and task-specific, limiting their adoption of modern multimodal experiments at the facility scale. Here we present IPSBrain, a unified AI-powered platform that serves as Intelligent Photon Source Brain for automated analysis of multimodal synchrotron experimental data. The platform integrated a series of novel, self-developed machine-learning-based models that enable automated data analysis from multiple experimental techniques, including diffraction, scattering, X-ray absorption, and tomograph. The platform is accessible through an intuitive web interface, which significantly lowers the technical barrier to advanced scientific data interpretation. By enabling end-to-end intelligent workflows from data acquisition to quantitative physical insight, IPSBrain supports high-throughput, reproducible, and scalable analysis aligned with the operational demands of modern synchrotron radiation sources. IPSBrain not only demonstrates a practical and extensible framework for AI-driven synchrotron data analysis but also establishes a transferable paradigm for intelligent data analysis of other large-scale research infrastructures, such as neutron sources and free-electron lasers.

The Journal of Physical Chemistry A
Beijing Institute of Technology (CN), Minzu University of China (CN), Chinese Academy of Sciences (CN), China University of Geosciences (Beijing) (CN), China Spallation Neutron Source (CN), Institute of High Energy Physics (CN), University of Chinese Academy of Sciences (CN), Spallation Neutron Source, PRG S&Tech (South Korea)
National Natural Science Foundation of China, Chinese Academy of Sciences, Institute of High Energy Physics, National Key Research and Development Program of China
Openalex Percentile: Top 5%
Nuclear Physics and Applications
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