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Hierarchically Structured Hydrogel Actuator for Microplastic Pollutant Detection and Removal
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Researchers developed a smart hydrogel actuator that can both detect and physically remove microplastic compound pollutants from water using light-driven movement. The device integrates hierarchical polymer networks that enable it to sense contamination and autonomously collect microplastic particles. The study demonstrates a novel approach to addressing aquatic microplastic pollution through self-powered soft robotics that combine sensing and remediation in a single material.
The aquatic microplastic pollution has aroused worldwide concerns due to its potential risk to biological and ecological health, especially the microplastic compound pollutants (MCPs) with amplified biotoxicity. Self-powered soft robots integrating with simultaneous MCP detection and removal capacities represent an intelligent way to clear the contaminants from water, but it is still challenging to implement these properties in one single actuating material. Here, we propose a smart light-driven hydrogel actuator with hierarchical interpenetrating networks consisting of covalently bonded polyethyleneimine and polydopamine copolymers, graphene oxide nanosheets, and poly(N-isopropylacrylamide) hydrogels, which function as adsorbents for MCPs, photothermal converters, and actuating matrix, respectively. Thanks to the integrative hierarchical structure design, the resulted actuator can behave like a soft swimming robot to simultaneously identify and adsorb MCPs, which successfully incorporates multiple functionalities without compromising the responsiveness. The hydrogel actuator features an ultralow detection limit (0.98 μM for the ferric ion), excellent adsorbing selectivity (97.09% for ferric ion-adsorbed MCPs), high adsorption (94.63%) and desorption efficiency (99.12%), and multiple and untethered photothermal actuation performances. We believe this work will shed light on a promising construction strategy of intelligent soft robots for environmental remediation applications.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.