An extremely high quantity of small pieces of synthetic polymers, namely, microplastics, has been recently identified in some of the most intact natural environments, e.g., on top of the Alps and Antarctic ice. This is a "scary wake-up call", considering the potential risks of microplastics for humans and marine systems. Sunlight-driven photocatalysis is the most energy-efficient currently known strategy for plastic degradation; however, attaining efficient photocatalyst-plastic interaction and thus an effective charge transfer in the micro/nanoscale is very difficult; that adds up to the common challenges of heterogeneous photocatalysis including low solubility, precipitation, and aggregation of the photocatalysts. Here, an active photocatalytic degradation procedure based on intelligent visible-light-driven microrobots with the capability of capturing and degrading microplastics "on-the-fly"in a complex multichannel maze is introduced. The robots with hybrid powers carry built-in photocatalytic (BiVO4) and magnetic (Fe3O4) materials allowing a self-propelled motion under sunlight with the possibility of precise actuation under a magnetic field inside the macrochannels. The photocatalytic robots are able to efficiently degrade different synthetic microplastics, particularly polylactic acid, polycaprolactone, thanks to the generated local self-stirring effect in the nanoscale and enhanced interaction with microplastics without using any exterior mechanical stirrers, typically used in conventional systems. Overall, this proof-of-concept study using microrobots with hybrid wireless powers has shown for the first time the possibility of efficient degradation of ultrasmall plastic particles in confined complex spaces, which can impact research on microplastic treatments, with the final goal of diminishing microplastics as an emergent threat for humans and marine ecosystems.
Bibliographical noteFunding Information:
This work was supported by the project Advanced Functional Nanorobots (reg. No. CZ.02.1.01/0.0/0.0/15_003/0000444 financed by the EFRR). We thank Katherine Villa for her contribution to the preparation of microrobots.
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All Science Journal Classification (ASJC) codes
- Materials Science(all)