image: Causal discovery from ARPES measurement data.
Credit: ©K. Fujita, K. Nakayama et al.
On December 23, 2025, Tohoku University and Fujitsu Limited announced the successful application of AI to derive new insights into the superconductivity mechanism of a new superconducting material. This demonstrates an important use case for AI technology in new materials development and suggests that the technology has the potential to accelerate research and development and drive innovation in various industries such as environment and energy, drug discovery and healthcare, and electronic devices. The AI technology was utilized to automatically clarify causal relationships from measurement data obtained at NanoTerasu Synchrotron Light Source This achievement was published in the Nature Portfolio scientific journal Scientific Reports on December 22, 2025.
To achieve this result, the two parties used Fujitsu's AI platform Fujitsu Kozuchi to develop a new discovery intelligence technique to accurately estimate causal relationships. Furthermore, in collaboration with the Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, the two parties applied this technology to data measured by angle-resolved photoemission spectroscopy (ARPES) (Note 1), an experimental method used in materials research, using a specific superconducting material as a sample.
Fujitsu will begin offering a trial environment for this technology in March 2026. Moving forward, both organizations will further leverage this technology along with NanoTerasu's world-class capabilities in spatial resolution to automatically clarify the causal relationships between phenomena at the microscopic level. This will contribute to the development of new functional materials that address global environmental issues - one of Fujitsu's materiality priorities - in areas such as high-temperature superconductivity and next-generation low-power consumption devices.
Background
Tohoku University and Fujitsu established the Fujitsu x Tohoku University Discovery Intelligence Laboratory in October 2022 as part of the Fujitsu Small Research Lab initiative which sees Fujitsu researchers stationed at universities to accelerate joint research, discover new themes, develop human resources, and build long-term relationships. The aim is to contribute to solving societal issues through the development of new technologies and human resource development, by integrating Tohoku University and Fujitsu’s technologies, achievements, and knowledge. The two parties are engaged in joint research to develop and socially implement discovery intelligence that uses AI to find solutions to various problems from data, including those in materials science.
NanoTerasu Synchrotron Light Source, which began operation in April 2024, enables the measurement of molecular, atomic, and electronic states with nanometer-level high spatial resolution. The facility works to develop new functional materials to drive innovation and contribute to resolving societal issues, including environmental challenges. However, as measurement performance improves, the amount of data created increases. Efficiently extracting only useful information without relying on human experience or intuition and advancing the automation of scientific research processes are key priorities for the future.
Technology features
- Significant compression of causal graph scale based on waveform parameter extraction
ARPES measurement data is very large. A causal graph of the data has a massive number of nodes making it difficult to find useful information. This technique significantly compresses the scale of the causal graph by performing fitting based on a model equation for the measurement data and constructing a causal graph from only the extracted parameters. - Causal graph simplification based on similarity calculation
To further facilitate the understanding of causal graphs, the two parties developed a technique to assess the similarity of pairs of highly correlated data items and remove redundant nodes. - Reduction of measurement noise impact by filtering estimated causal relationships by reliability, causal strength, and correlation coefficient
Among the estimated causal relationships, only those with reliability, causal strength, and correlation coefficient above a certain threshold are presented, thereby reducing the impact of measurement noise. This enables the extraction of causal relationships that are highly likely to be meaningful.
This technology reduced the size of the causal graph to less than 1/20 of the conventional size, enabling the efficient discovery of new insights.
Tohoku University and Fujitsu applied this technology to ARPES measurement data of cesium vanadium antimonide (CsV3Sb5), a kagome superconducting material. Cesium vanadium antimonide has potential applications as a high-temperature superconductor, but its superconductivity mechanism is not yet fully understood. The prevailing theories were that only vanadium electrons are involved, or that vanadium electrons and antimony electrons interact to achieve superconductivity. This initiative saw the extraction of causal relationship data from the measurement data of cesium vanadium antimonide, leading to the new insight that the chemical bonding state of cesium (Cs) atoms strongly influences the electronic state of the V3Sb5 layer, which is responsible for superconductivity in cesium vanadium antimonide. In other words, the superconductivity mechanism is due to the interaction of vanadium, antimony, and cesium electrons.
Notes:
(1) Angle-Resolved Photoemission Spectroscopy (ARPES):
An experimental method used in materials research to observe the state of electrons in a material by irradiating the crystal surface with ultraviolet light and simultaneously measuring the energy and momentum of electrons emitted outside the crystal due to the external photoelectric effect. In recent years, ARPES technology has advanced, making it possible to determine the real-space distribution of electronic structures by irradiating with ultraviolet light focused to a sub-micron diameter. This has enabled the observation of how the electronic structure of a material changes spatially.
Related Links
- NanoTerasu: https://nanoterasu.jp/top_en/
- Fujitsu Kozuchi: https://www.fujitsu.com/global/services/kozuchi/
- Fujitsu Small Research Lab: https://www.fujitsu.com/global/about/research/srl/
- Fujitsu x Tohoku University Discovery Intelligence Laboratory: https://www.mccs.tohoku.ac.jp/dil/index-e.html
About the Advanced Institute for Materials Research (WPI-AIMR)
Tohoku University
Establishing a World-Leading Research Center for Materials Science
AIMR aims to contribute to society through its actions as a world-leading research center for materials science and push the boundaries of research frontiers. To this end, the institute gathers excellent researchers in the fields of physics, chemistry, materials science, engineering, and mathematics and provides a world-class research environment.
AIMR site: https://www.wpi-aimr.tohoku.ac.jp/en/
About Fujitsu
Fujitsu’s purpose is to make the world more sustainable by building trust in society through innovation. As the digital transformation partner of choice for customers around the globe, our 113,000 employees work to resolve some of the greatest challenges facing humanity. Our range of services and solutions draw on five key technologies: AI, Computing, Networks, Data & Security, and Converging Technologies, which we bring together to deliver sustainability transformation. Fujitsu Limited (TSE:6702) reported consolidated revenues of 3.6 trillion yen (US$23 billion) for the fiscal year ended March 31, 2025 and remains the top digital services company in Japan by market share.
Find out more: global.fujitsu
Journal
Scientific Reports
Article Title
Extracting causality from spectroscopy
Article Publication Date
22-Dec-2025