Machine-learning-assisted prediction of the size of microgels prepared by aqueous precipitation polymerization DOI
Daisuke Suzuki, Haruka Minato,

Yuji Sato

и другие.

Chemical Communications, Год журнала: 2024, Номер 60(93), С. 13678 - 13681

Опубликована: Янв. 1, 2024

We report a linear-regression model that can predict microgel size using machine learning method, sparse modeling for small data.

Язык: Английский

In-Situ Characterization of Microgel Monolayers: Controlling Isostructural Phase Transitions for Homogeneous Crystal Drying Patterns DOI Creative Commons
Antonio Rubio-Andrés, Delfi Bastos‐González, Miguel Ángel Fernández-Rodríguez

и другие.

Journal of Colloid and Interface Science, Год журнала: 2025, Номер 688, С. 328 - 340

Опубликована: Фев. 22, 2025

Язык: Английский

Процитировано

1
Nano/microparticle-based tough and recyclable polymers toward a sustainable society DOI Creative Commons
Yuma Sasaki, Yuichiro Nishizawa, Takuma Kureha

и другие.

Chemical Communications, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

By virtue of their unique properties, polymer nano/microparticles constitute important building blocks for the construction functional nanomaterials.

Язык: Английский

Процитировано

0
Recent Trends for Functional Polymer Gels DOI
Daisuke Suzuki, Yuichiro Nishizawa

Kobunshi, Год журнала: 2025, Номер 74(3), С. 123 - 126

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Intermacromolecular Interaction Determines the Long-Ranged Force and Self-Assembly of Microgels at the Air/Water Interface DOI Creative Commons
Wei Liu,

Zuwei Zhao,

Li Zhang

и другие.

ACS Macro Letters, Год журнала: 2025, Номер unknown, С. 564 - 569

Опубликована: Апрель 21, 2025

We experimentally investigate the contribution of interchain interaction to interfacial stress and self-assembly microgels at air/water interface. Our results suggest that intercorona penetrations contribute an entropy-driven long-ranged force. The structural parameter binding energy between neighboring are given by using radial distribution function, which further clarifies intercore interactions during 2D phase transition.

Язык: Английский

Процитировано

0
Elastomer Particle Monolayers Formed by the Compression of Poly(methyl acrylate) Microparticles at an Air/Water Interface DOI Creative Commons
Yuma Sasaki, Yuichiro Nishizawa, Natsuki Watanabe

и другие.

Macromolecular Rapid Communications, Год журнала: 2024, Номер unknown

Опубликована: Сен. 25, 2024

Abstract In the previous study ( Green Chem ., 2023 , 25 3418), highly stretchable and mechanically tough poly(methyl acrylate) (pMA) microparticle‐based elastomers can be formed by drying a microparticle‐containing aqueous dispersion. This discovery has potential to overcome mechanical weakness of industrially produced latex films. However, in 3D‐arranged particle films, structural complexity, such as existence defects, makes it difficult clearly understand relationship between film structure its properties. this study, 2D‐ordered pMA monolayers at air/water interface Langmuir trough are prepared. Under high compression interface, microparticles contact their neighboring particles, resulting successfully transferred onto solid substrate. The monolayer films is linked an increase elastic modulus on substrate evident from local Young's mapping using atomic force microscopy. Thus, with different properties created trough.

Язык: Английский

Процитировано

2
Machine-learning-assisted prediction of the size of microgels prepared by aqueous precipitation polymerization DOI
Daisuke Suzuki, Haruka Minato,

Yuji Sato

и другие.

Chemical Communications, Год журнала: 2024, Номер 60(93), С. 13678 - 13681

Опубликована: Янв. 1, 2024

We report a linear-regression model that can predict microgel size using machine learning method, sparse modeling for small data.

Язык: Английский

Процитировано

1