EXTENDED ABSTRACT: The importance of "data" in materials development has been increasing in recent years, but efficiently cycling
through data generation, organization (accumulation), and utilization is not easy. At the Materials Fabrication and Analysis Platform [1]
within the Research Network and Facility Services Division of NIMS (National Institute for Materials Science), we support various research
and development by sharing NIMS's state-of-the-art equipment with a broad research community. To accelerate the sharing of data generated
here, it is important to discuss not only the types of data but also the experimental conditions necessary for data acquisition. We have been
working on defining unified conditions for various measurement methods and targets, and on structuring and storing data. By structuring data,
differences due to varying data formats can be absorbed through structuring processing. Therefore, at NIMS's Materials Data Platform [2], we have built Research Data Express (RDE). If RDE is operated effectively, it will become possible to utilize data from different experiments in an integrated and cross-sectional manner. For example, we can integrate measurement data of battery materials and magnetic materials or use XRD profiles and SEM image data together. By increasing the amount of usable data and utilizing it in a multimodal manner, we can improve the accuracy of predictive models by leveraging data science methods.Furthermore, NIMS offers a system called MatNavi, which organizes and records various materials data from experimental data, literature data, and other sources. To make computer-aided materials design more efficient, we are also developing a system (MInt) that solves forward problems in materials engineering at once based on the PSPP (Processing-Structure-Property-Performance) relationship, and a platform (pinax) for comprehensive AI analysis. Currently, these systems are being developed to operate independently, but in the future, through APIs, we aim to link data while leveraging the strengths of each system. By interconnecting each system for materials data analysis at NIMS and further connecting with domestic and international materials databases, we aim to maximize the advantages of system and data integration to accelerate materials development.
REFERENCEST:
[1] https://www.nims.go.jp/rnfs/en/materials-fabrication-and-analysis-platform/ (accessed on 1st July 2024)
[2] https://www.nims.go.jp/rnfs/en/materials-data-platform/ (accessed on 1st July 2024)
Received his Ph.D. from Tokyo Institute of Technology in March 2008 for his thesis on STM observation of Ag/Si surface structures; worked on thermodynamic calculations using ab initio and CALPHAD methods from 2000 to 2015; engaged in the development of the “MInt system” for structural materials research at NIMS since February 2015; since April 2018, he has been engaged in the development of fundamental technologies for the materials data platform; and since April 2024, he has been in his current position (Platform Director). In recent years, as represented by the field of materials informatics, the importance of “data” in materials development has been increasing, but efficiently circulating the generation, organization (accumulation), and use of data is not easy. The Materials Production and Analysis Platform[1] within the Research Network and Facilities Services Division of NIMS (National Institute for Materials Science) supports various research and development activities by sharing the cutting-edge equipment owned by NIMS with the wider research community. In order to accelerate the sharing of data generated here, it is important to express and store not only the type of data, but also the experimental conditions required to obtain the data. In terms of storage, structuring the data allows differences due to differences in data format to be absorbed. We have been working on structuring and storing data by defining uniform experimental conditions for various measurement methods and targets. To this end, the NIMS Materials Data Platform[2] has constructed Research Data Express (RDE). If RDE is used effectively as a storage location for structured data, it will be possible to use data from different experiments in a cross-sectional manner. For example, it will be possible to integrate measurement data from magnetic materials and battery materials to create a large database, or to use XRD profile and SEM image data in a multimodal manner. By increasing the amount of available data and using it in a variety of ways, it is hoped that the accuracy of prediction models can be improved using data science methods.In addition, NIMS provides a system called MatNavi that organizes and records various materials data, including experimental data and literature data. MatNavi is a data provision service that NIMS has been operating for many years, and it is continuously adding data and enhancing search functions. In addition, in order to make computer-aided materials design more efficient, we are also developing a system (MInt) that solves forward problems in materials engineering based on the PSPP (Processing-Structure-Property-Performance) relationship in one go, and a platform (pinax) that performs exhaustive analysis using AI.At present, these systems are being developed to operate independently, but in the future we aim to link the data of each system through APIs, making the most of the strengths of each system. By linking the various systems for analyzing material data at NIMS with each other and also with domestic and international material databases, we aim to accelerate material development by making the most of the benefits of integrating systems and data.