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Graphene-Based Microbots for Toxic Heavy Metal Removal and Recovery from Water
Open accessAbstract
Heavy metal contamination in water is a serious risk to the public health and other life forms on earth. Current research in nanotechnology is developing new nanosystems and nanomaterials for the fast and efficient removal of pollutants and heavy metals from water. Here, we report graphene oxide-based microbots (GOx-microbots) as active self-propelled systems for the capture, transfer, and removal of a heavy metal (i.e., lead) and its subsequent recovery for recycling purposes. Microbots' structure consists of nanosized multilayers of graphene oxide, nickel, and platinum, providing different functionalities. The outer layer of graphene oxide captures lead on the surface, and the inner layer of platinum functions as the engine decomposing hydrogen peroxide fuel for self-propulsion, while the middle layer of nickel enables external magnetic control of the microbots. Mobile GOx-microbots remove lead 10 times more efficiently than nonmotile GOx-microbots, cleaning water from 1000 ppb down to below 50 ppb in 60 min. Furthermore, after chemical detachment of lead from the surface of GOx-microbots, the microbots can be reused. Finally, we demonstrate the magnetic control of the GOx-microbots inside a microfluidic system as a proof-of-concept for automatic microbots-based system to remove and recover heavy metals.
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Cites
Removal of heavy metal ions from wastewaters: A review
Fu, F., & Wang, Q. (2011) · Journal of Environmental Management · doi:10.1016/j.jenvman.2010.11.011 · Cited by 8,703
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Parmar, J., Vilela, D., Villa, K., Wang, J., & Sánchez, S. (2018) · Journal of the American Chemical Society · doi:10.1021/jacs.8b05762 · Cited by 423
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Metadata
- Authors
- Vilela, D., Parmar, J., Zeng, Y., Zhao, Y., & Sánchez, S.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-03-24
- Volume
- 16
- Issue
- 4
- Pages
- 2860-2866
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2304206528
- Cited by
- 560
- References
- 1
- FWCI
- 45.58
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Vilela, D., Parmar, J., Zeng, Y., Zhao, Y., & Sánchez, S. (2016). Graphene-Based Microbots for Toxic Heavy Metal Removal and Recovery from Water. Nano Letters. https://doi.org/10.1021/acs.nanolett.6b00768
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
