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Critical Review of Advances in Engineering Nanomaterial Adsorbents for Metal Removal and Recovery from Water: Mechanism Identification and Engineering Design

期刊

ENVIRONMENTAL SCIENCE & TECHNOLOGY
卷 55, 期 8, 页码 4287-4304

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.0c07936

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资金

  1. Brook Byers Institute for Sustainable Systems, Hightower Chair
  2. Georgia Research Alliance at the Georgia Institute of Technology
  3. National Science Foundation Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment [EEC-1449500]

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Nanomaterial adsorbents show promise in removing toxic metals from water, but face challenges due to limited understanding of adsorption mechanisms and scaling up evaluation. Advanced tools and chemical principles can help identify mechanisms, while engineering issues must be addressed for successful implementation of NAs. Further research on microstructure properties and NA recovery from treated water is prioritized for development of efficient NAs.
Nanomaterial adsorbents (NAs) have shown promise to efficiently remove toxic metals from water, yet their practical use remains challenging. Limited understanding of adsorption mechanisms and scaling up evaluation are the two main obstacles. To fully realize the practical use of NAs for metal removal, we review the advanced tools and chemical principles to identify mechanisms, highlight the importance of adsorption capacity and kinetics on engineering design, and propose a systematic engineering scenario for full-scale NA implementation. Specifically, we provide in-depth insight for using density functional theory (DFT) and/or X-ray absorption fine structure (XAFS) to elucidate adsorption mechanisms in terms of active site verification and molecular interaction configuration. Furthermore, we discuss engineering issues for designing, scaling, and operating NA systems, including adsorption modeling, reactor selection, and NA regeneration, recovery, and disposal. This review also prioritizes research needs for (i) determining NA microstructure properties using DFT, XAFS, and machine learning and (ii) recovering NAs from treated water. Our critical review is expected to guide and advance the development of highly efficient NAs for engineering applications.

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