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.
Authors
- Haodong Yao (ORCID: https://orcid.org/0000-0001-5959-8594)
- Zuoxin Xi (ORCID: https://orcid.org/0000-0003-1237-7780)
- Liyuan Wu (ORCID: https://orcid.org/0000-0002-4890-2770)
- Yuan Qin (ORCID: https://orcid.org/0000-0002-5651-8293)
- Y W Sun (ORCID: https://orcid.org/0000-0002-4420-5708)
- Xiangwen Deng
- Lin Li
- Yihe Pang
- Jing Li
- Mengdan Han
- Lina Zhao (ORCID: https://orcid.org/0000-0002-9796-0221)
Institutions
- 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)
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
Funders
- National Natural Science Foundation of China
- Chinese Academy of Sciences
- Institute of High Energy Physics
- National Key Research and Development Program of China