December 5,2024
Nippon Paint Holdings Co., Ltd.

Elucidating the Link Between Polymer Material Strength and Structure

――Advancing New Painting Materials Development Through Molecular Dynamics Simulations and Mathematical Science Method――

Key Highlights:

• Introduced a novel analytical approach to uncover the relationship between polymer material strength and structure.
• Achieved automated extraction of structural factors linked to dynamic changes in material strength by applying mathematical science to data derived from molecular dynamics simulations of polymer film tension.
• This breakthrough enables efficient identification of key structural features influencing material strength, paving the way for designing next-generation materials, including innovative coating materials.

Unveiling Structural Determinants of Polymer Film Strength through Molecular Dynamics and Persistent Homology Analysis

Overview

 A research team led by Researcher Shinya Kawakami of Nippon Paint Co, Ltd., alongside Assistant Professor Ryuhei Sato and Professor Yasushi Shibuta from the School of Engineering, the University of Tokyo has pioneered a novel approach to uncover the relationship between the structure and strength of polymer materials by combining molecular simulations with advanced mathematical science techniques.
In this research project, we successfully identified the microscopic structures governing the strength of polymer films by integrating molecular dynamics simulations (Note 1) performed on supercomputers with the mathematical science technique of persistent homology analysis (Note 2).
 This approach is groundbreaking as it does not rely on prior learning with similar datasets, unlike conventional machine learning methods. It autonomously and efficiently uncovers the relationship between material strength and structure without requiring preliminary knowledge. These advancements are poised to drive significant progress in the design and development of innovative materials, including advanced coatings.
 The findings of this study are scheduled for publication in the Journal of Chemical Theory and Computation, a journal of the American Chemical Society, on December **, 2024 (local time).

Announcement Details

 The paint industry continues to rely heavily on organic solvents for many of its coatings. However, due to increasing environmental and safety concerns, there is a significant shift toward water-based paints, with demand rising steadily each year. In paint development, controlling the strength properties of paint materials is essential, particularly for ensuring durability and performance. While conventional technologies allow for the measurement of polymer strength properties, they fall short in elucidating the relationship between specific internal structures and these properties. As a result, material design has traditionally depended on empirical rules rather than precise structural insights.
 In this research project, we performed molecular dynamics simulations of tensile tests on polymer films using a supercomputer. To analyze the structural changes occurring in the polymer films during these tensile tests, we applied the mathematical science technique of persistent homology analysis. Persistent homology analysis (Figure 1, left) provides a means to capture the structural properties of polymer films by tracking the formation and disappearance of "rings" or "holes." These are geometric features formed by expanding the atomic radii within the polymer film and connecting the atoms. For instance, polymer films composed of chains with different lengths produce distinct distributions in their persistence diagrams (Note 2) (Figure 1, right), highlighting their unique structural differences.

Figure 1: (Left) Overview of Persistent Homology; (Right) Example of a Persistent Diagram for Polymer

 During the tensile tests of polymer films, the persistence diagram revealed ring structures with the most significant changes. These changes were found to correspond to fluctuations in stress observed in the stress-strain curve (Note 3, Figure 2, top right). Furthermore, through reverse analysis of the persistence diagrams (Note 4), we successfully identified specific polymer chain structures that influence the stress-strain behavior (Figure 2, bottom right). While traditional machine learning methods can predict strength characteristics from material structures, they face challenges in reverse analysis to pinpoint the structural factors governing these properties. Our study addresses this limitation by leveraging persistent homology analysis to automatically extract the structural factors controlling material strength under tensile conditions. This approach allows for the efficient extraction of strength-related information from polymer material simulations. It significantly reduces the resources, time, cost, and environmental impact involved, thereby contributing to the development of innovative coatings materials.

This research project was conducted as part of the collaborative research initiatives within the social collaboration program “Creation of Innovative Coating Technologies.” This program was established under an industry-academia co-creation agreement between the University of Tokyo and Nippon Paint Holdings. The program is set to run for five years, from October 1, 2020, to September 30, 2025.

Figure 2: (Left) Analysis Results from Molecular Dynamics Simulations andPersistent Homology;
                                    (Right) Identification of Structural Factors Influencing the Stress-Strain Curve via Reverse Analysis

Authors and Researchers　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　 　　　　 　　

- Department of Materials Engineering, School of Engineering, The University of Tokyo

- Ryuhei Sato Assistant Professor
- Yasushi Shibuta Professor
- Takanori Ichiki Professor
  Concurrent：Research Director, Innovation Center of NanoMedicine, Kawasaki Institute of Industry Promotion
- Hirotaka Ejima Associate Professor 

- NIPPON PAINT CO., LTD. Technology Division

- Shinya Kawakami Researcher, Research & Development Department Advanced Product Development Group
- Takahiro Ujii Researcher, Group Leader, Research & Development Department Advanced Product Development
- Koichi Sato Researcher, Deputy Division Director and General Manager, Research & Development Department

The Details of Research Paper　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　 　　　　 　　

Magazine name: Journal of Chemical Theory and Computation
Title: Dynamic Correlation Analysis between Stress-Strain Curve and Polymer Film Structure Using Persistent Homology
Authors: Ryuhei Sato*, Shinya Kawakami, Hirotaka Ejima, Takahiro Ujii, Koichi Sato, Takanori Ichiki, Yasushi Shibuta
DOI: 10.1021/acs.jctc.4c01418
URL: https://doi.org/10.1021/acs.jctc.4c01418

Glossary of Terms

(Note 1) Molecular Dynamics Simulations

A computational technique used to study the behavior of materials at the atomic level by solving the equations of motion. By calculating the forces acting on each atom, along with their initial positions and velocities, the method determines the unique positions and velocities of all atoms at any given time.

(Note 2) Persistent Homology

A mathematical technique used to analyze the shape and structure of discrete data across multiple scales by adjusting the resolution. It identifies and quantifies features such as holes, voids, and connected components, extracting geometric information efficiently. The resulting visualization, which plots the parameters (e.g., size) at which these features (such as rings or holes) appear and disappear, is known as a persistence diagram.

(Note 3) Stress-Strain Curve

A graphical representation of the relationship between stress and strain during tensile testing of materials. It provides key mechanical properties, such as Young’s modulus and tensile strength.

(Note 4) Reverse Analysis

A method used to deduce the underlying parameters or conditions responsible for observed outcomes. In this study, it specifically refers to the process of identifying the atomic structures that correspond to the unique geometric features extracted through persistent homology analysis.