研究紹介
研究テーマ
Rational in-silico design of polymer networks
キーワード
Polymer Physics, Soft Materials, Computational Physics, Molecular Dynamics, Multi-scale Modeling, Machine Learning
研究概要
My research interests lie in understanding complex systems. I have been working on problems related to polymer physics and soft matter by means of theoretic tools, computational techniques, and numerical methods. My research goals are to advance the state-of-the-art theory and simulation tools in the field and to provide insightful guidance and innovative strategies for functional applications in smart materials, biomedical engineering, and energy storage. My current research focuses on studying mechanical properties of polymer networks through theory and molecular dynamics simulations.
代表的な研究成果
- Self-Consistent Field Theory Study of Polymer-mediated Colloidal Interactions in Solution: Depletion Effects and Induced Forces
W. Li, K. Delaney, G. Fredrickson. J. Chem. Phys., 2021, 155, 154903.
DOI: 10.1063/5.0065742 - Dynamics of Long Entangled Polyisoprene Melts via Multiscale Modeling
W. Li, P. K. Jana, A. Behbahani, G. Kritikos, L. Schneider, P. Polińska, C. Burkhart, V. Harmandaris, M. Müller, M. Doxastakis. Macromolecules, 2021, 54, 8693–8713.
DOI: 10.1021/acs.macromol.1c01376 - Glass Transition of Ion-containing Polymer Melts in Bulk and Thin Films
W. Li, M. Olvera de la Cruz. Soft Matter, 2021, 17, 8420-8433.
DOI: 10.1039/D1SM01098K - Tailoring Interfacial Properties in Polymer-Silica Nanocomposites via Surface Modification: An Atomistic Simulation Study.
W. Li, P. Bacova, A. Behbahani, C. Burkhart, P. Polińska, V. Harmandaris, M. Doxastakis. ACS Applied Polymer Materials, 2021, 3, 2576–2587.
DOI: 10.1021/acsapm.1c00197 - Backmapping Coarse-grained Macromolecules: An Efficient and Versatile Machine-learning Approach
W. Li, C. Burkhart, P. Polińska, V. Harmandaris, M. Doxastakis. J. Chem. Phys., 2020, 153, 041101.
DOI: 10.1063/5.0012320
関連する研究記事
- プレスリリース 超強⼒接着性ハイドロゲルのデノボ設計に成功! 〜データ駆動型アプローチで材料開発の新境地を開拓〜
- プレスリリース 化学結合の切断を利用した新しい自己強化材料の開発 ~機械化学反応による急速強化が可能に~
業績一覧
2025年
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Rapid Self-Strengthening in Double-Network Hydrogels Triggered by Bond Scission
, W. Li, X. Li, T. Nakajima, M. Rubinstein, J. Gong, NATURE MATERIALS, 2025, ,
DOI: 10.1038/s41563-025-02137-6
2024年
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Boosting the Strength and Toughness of Polymer Blends via Ligand-Modulated MOFs
, H. Guo, W. Guo, W. Liu, W. Li, M. Saeb, M. Vatankhah-Varnosfaderani, S. Sheiko, Advanced Science, 2024, ,
DOI: 10.1002/advs.202407593
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Tuning Network Structures of Hydrophobic Hydrogels by Controlling Polymerization Solvent
, D. Naohara, W. Li, X. Li, J. P. Gong, Polym. Chem., 2024, ,
DOI: 10.1039/d4py00256c
2023年
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Molecular Dynamics Simulations of Ideal Living Polymerization: Terminal Model and Kinetic Aspects
, J. Phys. Chem. B, 2023, 127, 35, 7624–7635
DOI: 10.1021/acs.jpcb.3c03126
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Polymer Brush Inspired by Ribosomal RNA Transcription
, W. Li, European Physical Journal E, 2023, 46, 61
DOI: 10.1140/epje/s10189-023-00323-5
2022年
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Deep Convolutional Neural Networks for Generating Atomistic Configurations of Multi-Component Macromolecules from Coarse-Grained Models
, A. Chazirakis, C. Chrysostomou, M. A. Nicolaou, W. Li, M. Doxastakis, V. A. Harmandaris, J. Chem. Phys., 2022, 157, 184903
DOI: 10.1063/5.0110322