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

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

Článek WoS

Electroactive membranes can dynamically regulate interfacial properties using external electric potentials, which offers a feasible approach to preventing fouling and controlling selective separation performance in water treatment. However, current pre-programmed control modes struggle to adapt to the dynamic changes in membrane interface states, fouling characteristics, and water quality during filtration processes. Improper regulation may lead to suboptimal performance, increased energy consumption, and even accelerated membrane aging. This paper argues that transitioning from static functional materials to environmentally adaptive intelligent systems is the key pathway to unlocking the potential of electroactive membranes. We propose evolving from pre-programmed execution to intelligent operation based on "real-time sensing-prediction-optimization". By diagnosing microfouling early and identifying intrinsic characteristics, we can predict the quantitative impact of regulatory measures on short-term performance and long-term lifespan. Through continuous self-evolution, the system actively seeks global optimal solutions, synergistically maximizing separation stability and material longevity while minimizing energy consumption footprint. This paper systematically outlines the theoretical foundation, core components, and operational logic of this intelligent framework, while identifying key future research directions and technological development pathways.

Electroactive membranes can dynamically regulate interfacial properties using external electric potentials, which offers a feasible approach to preventing fouling and controlling selective separation performance in water treatment. However, current pre-programmed control modes struggle to adapt to the dynamic changes in membrane interface states, fouling characteristics, and water quality during filtration processes. Improper regulation may lead to suboptimal performance, increased energy consumption, and even accelerated membrane aging. This paper argues that transitioning from static functional materials to environmentally adaptive intelligent systems is the key pathway to unlocking the potential of electroactive membranes. We propose evolving from pre-programmed execution to intelligent operation based on "real-time sensing-prediction-optimization". By diagnosing microfouling early and identifying intrinsic characteristics, we can predict the quantitative impact of regulatory measures on short-term performance and long-term lifespan. Through continuous self-evolution, the system actively seeks global optimal solutions, synergistically maximizing separation stability and material longevity while minimizing energy consumption footprint. This paper systematically outlines the theoretical foundation, core components, and operational logic of this intelligent framework, while identifying key future research directions and technological development pathways.

Electroactive membrane, Intelligent control, Reinforcement learning, Hybrid predictive model, Membrane fouling control

Electroactive membrane, Intelligent control, Reinforcement learning, Hybrid predictive model, Membrane fouling control

Yao Xu, Luyang Zhao, Fangchao Zhao, Rusen Zou, Qipeng Zhao, Huaqiang Chu, Dapeng Li, Xuexiu Jia, Jingqiu Sun, Xuefei Zhou, Yalei Zhang

01.08.2026

Elsevier

Water research

300

8

Spojené království Velké Británie a Severního Irska

9

https://www.sciencedirect.com/science/article/pii/S0043135426006378#ack0001