The IWSN 2026 conference became a platform for young scientists to acquire professional knowledge and skills, exchange experience, and discuss the results of scientific work obtained using synchrotrons. The program included lectures by leading global experts, oral and poster presentations, as well as practical master classes led by experts.

This year, the conference focused on three key areas: artificial intelligence for experiment management and real‑time data processing, machine learning, and supercomputer modeling; materials diagnostics in situ and operando mode using synchrotron radiation sources; and smart materials: synthesis, nanotechnologies, and development prospects.

Opening the event, Professor Alexander Soldatov, Director of the International Research Institute of Smart Materials at SFedU, emphasized that the IWSN school consistently brings together the most pressing topics — from new materials to digital methods of experiment management. Young scientists here gain not just theory, but real experience working with equipment and data, without which it is impossible to imagine science at mega‑class facilities today.

“The holding at the Southern Federal University of the School for Young Scientists in the Field of Synchrotron Research – IWSN, which has already become a regular event, this year had its own specifics: during the School, a number of master classes were held on a topic that is extremely relevant at the present time – the use of digital assistants (modern artificial intelligence technologies) for processing large datasets obtained during operando studies at synchrotron radiation sources and in the field of new materials development,” noted Alexander Soldatov.

In his report, he emphasized the importance of integrating artificial intelligence into the operation of stations at synchrotron radiation (SR) sources so that researchers would leave the experiment not with a set of data, but with a solution to their problem.

Of particular interest to the participants were the master classes devoted to the use of AI agents for analyzing data operando and in situ diagnostics in real time, as well as the use of microfluidic systems for the synthesis and diagnostics of reaction mixtures. The participants solved real‑world problems: from working with large language models (LLM) to PCA analysis and spectrum clustering. To maximize efficiency, each participant was provided with access to the Blokhin supercomputer and specialized AI agents.

Among the conference participants were staff from the International Research Institute of Intellectual Materials of Southern Federal University, the Research Institute of Physics of Southern Federal University, and the Faculty of Chemistry of Southern Federal University, as well as scientists from Voronezh State University, the Institute of Physics of the Herzen Russian State Pedagogical University, the Research Center “Kurchatov Institute,” the SKIF Common Use Center, the Sirius Scientific and Technological University, institutes of the Ural Branch of the Russian Academy of Sciences, and other scientific centers. The geographical reach of the participants included not only Russia but also India, Africa, Egypt, and China. Some researchers traditionally participated in a remote format. 

Following the conference, the “Collection of Abstracts” was posted on the official IWSN 2026 website; it presents the research results of young scientists. The collection is also available via the link – IWSN 2026 Abstracts Collection 21.07.26.pdf — Yandex Disk.

The organization of the international school was carried out within the framework of the Ministry of Education and Science as part of the project “Development of infrastructure for smart operando diagnostic stations using synchrotron radiation sources and their implementation at the MUR KISI” under Agreement No. 075-15-2025-509 dated May 30, 2025.