News Release

Automated simulation software creates a world map of polymer properties

Peer-Reviewed Publication

Research Organization of Information and Systems

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image: RadonPy is a first open-source Python library that can fully automate polymer physical property calculations using simulations of classical molecular dynamics based on atomistic models. view more 

Credit: © The Institute of Statistical Mathematics

The team published their method and experimental validation on Nov. 8 in npj Computational Materials.

“Materials informatics (MI), a new branch of materials research that combines materials data with data science, is gaining traction,” said co-corresponding author Yoshihiro Hayashi, assistant professor, Institute of Statistical Mathematics in the Research Organization of Information and Science (ROIS). Hayashi is also affiliated with the University of Tokyo’s Department of Mechanical Engineering. “MI applies machine learning to predict new materials with innovative properties and their fabrication methods from a vast design space. As such, data is the most important resource in MI.”

Despite the need, Hayashi said, efforts to create a comprehensive database of polymer properties to enable data-driven research have fallen short.

“To construct a database of polymer properties by molecular simulations, we developed RadonPy,” Hayashi said. “It’s the first open-source software that successfully automates polymer physical property calculations using simulations of classical molecular dynamics based on atomistic models — which account for the behaviors and characteristics of individual constituents.”

The program takes an assigned polymer and runs calculations to equilibrate it in prescribed system parameters. Once it does, it can then calculate the polymer’s density, radius of gyration, refractive index, thermal conductivity, specific heat capacities at constant pressure and at constant volume, among other information. RadonPy produces and stores the data, which can then be accessed later. The researchers also implemented a machine learning technique called transfer learning to correct biases and variations between the simulated property values and experimental data.

“In this study, more than 1,000 unique amorphous polymers were computed in about two months, mainly using the supercomputer Fugaku,” said co-corresponding author Ryo Yoshida, professor, Institute of Statistical Mathematics in ROIS, the National Institute for Materials Science’s Research and Services Division of Materials Data and Integrated System and The Graduate University of Advance Studies’ Department of Statistical Science. “The program implements a set of automatic computation functions for 15 different properties, which were systematically compared with experimental data to validate the calculation conditions. We also comprehensively verified the agreement between six properties obtained from high-throughput molecular dynamics calculations and experimental values.”

The research team also identified eight amorphous polymers with high conductivity, according to Yoshida. Now, the group is using RadonPy to create the world’s largest open database of polymer physics, with more than 100,000 different polymer species. In addition to ROIS, three universities and 19 companies are partnering to jointly develop other databases with RadonPy for a variety of applications in academia and industry.

“This project will create a world map of polymer material properties,” Hayashi said. “Such exhaustive observations cannot be achieved solely via experimental approaches requiring considerable costs, such as in material synthesis. This research is the first step toward a new horizon of polymer science.”

Other contributors include Junichiro Shiomi and Junko Morikawa, both affiliated with the Institute of Statistical Mathematics in ROIS. Shiomi is also affiliated with the University of Tokyo’s Department of Mechanical Engineering and Institute of Engineering Innovation. Morikawa is also affiliated with the Department of Materials Science and Engineering in the Tokyo Institute of Technology’s School of Materials and Chemical Technology.

The Japan Science and Technology Agency; the Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science and the JPCI System Research Project supported this research.

 

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About The Institute of Statistical Mathematics (ISM)

The Institute of Statistical Mathematics (ISM) is part of Japan's Research Organization of Information and Systems (ROIS). With more than 75 years of history, the institute is an internationally renowned facility for research on statistical mathematics including comprehensive evaluation of earthquake data in Japan and other parts of the world. ISM comprises three different departments including the Department of Statistical Modeling, the Department of Statistical Data, and the Department of Statistical Inference and Mathematics, as well as several key data and research centers. Through the efforts of various research departments and centers, ISM aims to continuously facilitate cutting edge research collaboration with universities, research institutions, and industries both in Japan and other countries.


About the Research Organization of Information and Systems (ROIS)

ROIS is a parent organization of four national institutes (National Institute of Polar Research, National Institute of Informatics, the Institute of Statistical Mathematics and National Institute of Genetics) and the Joint Support-Center for Data Science Research. It is ROIS's mission to promote integrated, cutting-edge research that goes beyond the barriers of these institutions, in addition to facilitating their research activities, as members of inter-university research institutes.


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