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Making waves: Toward an intelligent operating paradigm for electroactive membrane systems.

Yao Xu1, Luyang Zhao2, Fangchao Zhao3

  • 1School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; College of Environment and Safety Engineering, Fuzhou University, Fuzhou 350108, China.

Water Research
|April 21, 2026
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Summary
This summary is machine-generated.

Electroactive membranes can improve water treatment by adapting to changing conditions. An intelligent, real-time sensing, prediction, and optimization system enhances performance and membrane lifespan.

Keywords:
Electroactive membraneHybrid predictive modelIntelligent controlMembrane fouling controlReinforcement learning

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Area of Science:

  • Membrane science and technology
  • Water treatment technologies
  • Smart materials

Background:

  • Electroactive membranes offer dynamic control over interfacial properties for water treatment.
  • Current control modes are pre-programmed and fail to adapt to dynamic fouling and water quality changes.
  • This leads to suboptimal performance, increased energy use, and membrane aging.

Purpose of the Study:

  • To propose a shift from static electroactive membranes to adaptive intelligent systems.
  • To develop an intelligent operation framework based on real-time sensing, prediction, and optimization.
  • To address the limitations of current pre-programmed control modes in electroactive membrane applications.

Main Methods:

  • Developing a framework for intelligent operation of electroactive membranes.
  • Implementing early microfouling diagnosis and characteristic identification.
  • Utilizing predictive modeling for regulatory measure impact assessment.
  • Employing continuous self-evolution for system optimization.

Main Results:

  • The proposed intelligent system enables early microfouling detection and characteristic identification.
  • Predictive capabilities allow for quantitative assessment of regulatory impacts on performance and lifespan.
  • Continuous self-evolution optimizes separation stability, material longevity, and energy efficiency.

Conclusions:

  • Transitioning to intelligent, adaptive systems is crucial for unlocking the full potential of electroactive membranes.
  • The "real-time sensing-prediction-optimization" framework offers a pathway to synergistic improvements in water treatment.
  • Future research should focus on developing and validating this intelligent framework for practical applications.