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Researchers from the University of Tokyo and their collaborators have developed a digital laboratory system which fully automates the synthesis of materials and the evaluation of the structural and physical properties of thin layers. With the digital laboratory, or DLAB, the team can autonomously synthesize thin film samples and measure their materials of materials. The system demonstrates an advanced synthesis of automatic and autonomous materials for data science focused on data and robots.
Current research is published in the journal Digital discovery.
Automatic learning, robotics and data are considered essential to discover new materials. However, although data collection is an essential component, there is a bottleneck in this part of the experimental process.
Thus, the researchers built a digital laboratory with interconnected devices for research on solid materials. They used robots to collect experimental data, such as synthesis processes and measured physical properties, including measurement conditions. Their DLAB consists of a variety of modular experimental instruments which are physically interconnected. This allows researchers to completely automate the processes of the synthesis of materials to a wide range of measurements for surface microstructures, X -ray diffraction models, raman spectra (a chemical analysis technique using diffused light), electrical conductivity and optical transmittance.
The DLAB consists of two systems. A system incorporates experimental instruments to synthesize and automated materials, while the other manages data collection and analysis. Each measurement instrument provides data released in XML format data storage called Maiml, which is collected in a cloud -based database. Then the data is analyzed by the software and used on the cloud.
“We have shown that the system can independently synthesize a thin layer material specified by a researcher,” said Professor Taro Hitosugi of Graduate School of Science at Tokyo University. Using DLAB, his team has demonstrated the autonomous synthesis of thin movies of positive electrode to lithium-ion and their structural evaluation via measurements of X-ray diffraction motifs.
In recent years, automatic learning and robotics have provided researchers with new ways to carry out automatic and autonomous experiences. “Today, laboratories are not simply the places to house experimental instruments, but rather the production factories of materials and data, where experimental equipment works as a system,” said Hitosugi.
By assigning repetitive experimental tasks to the robot systems controlled by automatic learning, researchers can synthesize, measure and analyze a large number of samples, thus generating in -depth data. This science focused on data and robots, as well as the standardization of the summary and measurement instruments of materials, and the automation of data collection, will have a significant impact on the way research is carried out.
“Our current work is part of the challenges of accelerating research in materials science,” said Hitosugi. “Our approach improves the use of data in research. We aim to create a research environment where researchers can focus on creativity. The introduction of automatic learning and robotics will make the science of materials progress, will deepen the theory and the search for new materials. ”
However, even with recent progress, modularization and normalization of research on solid materials are still rudimentary. A factor that contributes to it is the lack of standards established for the shapes and sizes of samples and samples holders. Solid materials are available in a variety of physical forms, including forms of powder and bulk. Researchers need standardized samples and sampling holders. A unified format for measurement data is also lacking, complicating data collection. The Japan Analytical Instruments Manufacturers Association (JAIMA) has collaborated with member companies and the Ministry of Economy, Trade and Industry, to establish a data format called the marking language of measurement analysis instruments (Maiml). Maiml was recorded as the Japanese industrial standard in 2024. This standardized format provides a unified format for the collection and use of data.
For the future, the team hopes to improve the system by normalizing orchestration software and planning. This would allow researchers to extend the explorations of materials and more effectively manage the tasks of several samples. Their objective is to take advantage of the DLAB to accelerate the development of materials. “We aim to digitize the research and development environment, promoting researchers who can use these technologies and facilitate the sharing and use of data,” said Kazunori Nishio, collaboration researcher, an associate teacher specially appointed to the Institut des Sciences Tokyo. “This environment will take full advantage of the creativity of researchers.”
Reference: Nishio K, Aiba A, Takihara K, et al. A digital laboratory with a modular measurement system and a standardized data format. Digit Disnov. 2025: 10.1039.D4DD00326H. DOI: 10.1039 / D4DD00326H
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