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<p>In this study, an innovative multi-scale research framework integrating molecular dynamics (MD) simulations, machine learning (ML) prediction, and experimental validation was established to systematically elucidate the mechanism by which polyvinylpyrrolidone (PVP) regulates the performance and structure-property relationship of phenolphthalein-based polyether ether ketone/polyethyleneimine (PEEKWC/PEI) ultrafiltration membranes. MD simulations further revealed at the atomic scale that PVP forms a hydrogen-bonding network with the membrane matrix via the carbonyl oxygen of the pyrrolidone ring, thereby significantly enhancing interfacial compatibility. Its flexible chain intercalation can increase the free volume of the membrane. However, excessive addition induces local aggregation and entanglement of molecular chains, hindering water molecule diffusion, resulting in a decrease in diffusion coefficient from 0.115 Ų/ps to 0.082 Ų/ps. The ML model accurately reproduced the decreasing trend of water flux with the increase of PVP content. Combined with SHAP analysis to quantify the influence weight of each factor, it was clarified that operating pressure and surface roughness are the dominant factors, and the global optimal PVP addition amount was identified. Experimental validation showed that the PVP-K90 modified membrane exhibits the best comprehensive performance, with a pure water flux of up to 3162.1&#xa0;L·m<sup>-2</sup>·h<sup>-1</sup>, a Congo Red (CR) rejection rate of 95.3%, and a flux recovery rate (FRR) of 88.9%, demonstrating excellent antifouling performance. The PVP-K120 modified membrane shows better dye rejection effect in high-salt environments, with a rejection rate exceeding 87%. This study moves beyond the traditional trial-and-error approach, reveals the microscopic essence of additive effects through multi-scale correlation analysis, not only successfully prepares high-performance ultrafiltration membranes, but also provides a replicable innovative research paradigm for the directed design and performance optimization of separation membranes.</p>

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Multi-Scale Analysis of PVP-Regulated PEEKWC/PEI Ultrafiltration Membranes for Dye Wastewater Treatment

  • 期刊论文

  • 发表日期：

    2026年7月25日

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  • Xiaoyu Yang,
  • Yunwu Yu,
  • Hailong Zhou,
  • Qicheng Xu,
  • Xiaowei Sun,
  • Yan Wang,
  • Peng Liu,
  • Ting Li,
  • Xin Liu,
  • Lili Gao

摘要

In this study, an innovative multi-scale research framework integrating molecular dynamics (MD) simulations, machine learning (ML) prediction, and experimental validation was established to systematically elucidate the mechanism by which polyvinylpyrrolidone (PVP) regulates the performance and structure-property relationship of phenolphthalein-based polyether ether ketone/polyethyleneimine (PEEKWC/PEI) ultrafiltration membranes. MD simulations further revealed at the atomic scale that PVP forms a hydrogen-bonding network with the membrane matrix via the carbonyl oxygen of the pyrrolidone ring, thereby significantly enhancing interfacial compatibility. Its flexible chain intercalation can increase the free volume of the membrane. However, excessive addition induces local aggregation and entanglement of molecular chains, hindering water molecule diffusion, resulting in a decrease in diffusion coefficient from 0.115 Ų/ps to 0.082 Ų/ps. The ML model accurately reproduced the decreasing trend of water flux with the increase of PVP content. Combined with SHAP analysis to quantify the influence weight of each factor, it was clarified that operating pressure and surface roughness are the dominant factors, and the global optimal PVP addition amount was identified. Experimental validation showed that the PVP-K90 modified membrane exhibits the best comprehensive performance, with a pure water flux of up to 3162.1 L·m-2·h-1, a Congo Red (CR) rejection rate of 95.3%, and a flux recovery rate (FRR) of 88.9%, demonstrating excellent antifouling performance. The PVP-K120 modified membrane shows better dye rejection effect in high-salt environments, with a rejection rate exceeding 87%. This study moves beyond the traditional trial-and-error approach, reveals the microscopic essence of additive effects through multi-scale correlation analysis, not only successfully prepares high-performance ultrafiltration membranes, but also provides a replicable innovative research paradigm for the directed design and performance optimization of separation membranes.