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<p>The multiscale correlation between molecular-level characteristics and macroscopic material properties remains a fundamental challenge in chemistry and materials science. Here, we demonstrate a cross-scale investigation bridging single-molecule interactions and viscosity of liquid polycarbosilane (LPCS) by using single-molecule break junction techniques with artificial-intelligence-based unsupervised data clustering approaches. We investigated the supramolecular junction formation probability in oligomeric carbosilanes (OCS) with different architectures to reveal the connection between molecular structure and intermolecular interactions. Our results demonstrate that increasing carbon chain length, introducing oxygen atoms, reducing conjugation, and elevating the C/Si ratio can enhance the intermolecular forces of OCS. Moreover, viscosity measurements of corresponding synthesized LPCS show consistent trends with junction formation probabilities of supramolecular junctions at the single-molecule scale. By establishing intermolecular interactions as the bridge, we constructed an intrinsic connection between molecular structure and macroscopic rheological properties of polymers, which provides a foundation for cross-scale prediction and optimization of material properties from the molecular level.</p>

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Cross-scale transfer from single-molecule intermolecular interactions to viscosity of polymers

  • 期刊论文

  • 发表日期：

    2026年1月4日

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  • Jidong Hu,
  • Yang Yi,
  • Zuzhang Lin,
  • Mingbin Gao,
  • Ning Cao,
  • Juejun Wang,
  • Huacheng Sun,
  • Jingshu Wu,
  • Yinyin Shi,
  • Shenglun Xiong,
  • Jieyao Lv,
  • Jie Bai,
  • Wenjing Hong

摘要

The multiscale correlation between molecular-level characteristics and macroscopic material properties remains a fundamental challenge in chemistry and materials science. Here, we demonstrate a cross-scale investigation bridging single-molecule interactions and viscosity of liquid polycarbosilane (LPCS) by using single-molecule break junction techniques with artificial-intelligence-based unsupervised data clustering approaches. We investigated the supramolecular junction formation probability in oligomeric carbosilanes (OCS) with different architectures to reveal the connection between molecular structure and intermolecular interactions. Our results demonstrate that increasing carbon chain length, introducing oxygen atoms, reducing conjugation, and elevating the C/Si ratio can enhance the intermolecular forces of OCS. Moreover, viscosity measurements of corresponding synthesized LPCS show consistent trends with junction formation probabilities of supramolecular junctions at the single-molecule scale. By establishing intermolecular interactions as the bridge, we constructed an intrinsic connection between molecular structure and macroscopic rheological properties of polymers, which provides a foundation for cross-scale prediction and optimization of material properties from the molecular level.