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The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Rapid, Selective Extraction of Trace Amounts of Gold from Complex Water Mixtures with a Metal–Organic Framework (MOF)/Polymer Composite

Open access
Sun, Daniel T., Gasilova, Natalia, Yang, Shuliang, Oveisi, Emad, Queen, Wendy L.·2018·Journal of the American Chemical Society

Abstract

With the ever-increasing production of electronics, there is an ensuing need for gold extraction from sources other than virgin mines. Currently, there are no technologies reported to date that can effectively and selectively concentrate ultratrace amounts of gold from liquid sources. Here, we provide a blueprint for the design of several highly porous composites made up of a metal-organic framework (MOF) template and redox active, polymeric building blocks. One such composite, Fe-BTC/PpPDA, is shown to rapidly extract trace amounts of gold from several complex water mixtures that include wastewater, fresh water, ocean water, and solutions used to leach gold from electronic waste and sewage sludge ash. The material has an exceptional removal capacity, 934 mg gold/g of composite, and extracts gold from these complex mixtures at record-breaking rates, in as little as 2 min. Further, due to the high cyclability, we demonstrate that the composite can effectively concentrate gold and yield purities of 23.9 K.

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Crossref · 10.1021/jacs.8b09555

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Metadata

Authors
Sun, D. T., Gasilova, N., Yang, S., Oveisi, E., & Queen, W. L.
Venue
Journal of the American Chemical Society
Published
2018-11-05
Volume
140
Issue
48
Pages
16697-16703
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2900224875
Cited by
366
References
24
FWCI
7.72
Type
journal article
Language
en
Open access
hybrid

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.