Highly efficient and selective extraction of gold by reduced graphene oxide

Fei Li, Jiuyi Zhu, Pengzhan Sun, Mingrui Zhang, Zhenqing Li, Dingxin Xu, Xinyu Gong, Xiaolong Zou, A. K. Geim (), Yang Su () and Hui-Ming Cheng ()
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Fei Li: Tsinghua University
Jiuyi Zhu: Tsinghua University
Pengzhan Sun: University of Manchester
Mingrui Zhang: Tsinghua University
Zhenqing Li: Tsinghua University
Dingxin Xu: Tsinghua University
Xinyu Gong: Tsinghua University
Xiaolong Zou: Tsinghua University
A. K. Geim: Tsinghua University
Yang Su: Tsinghua University
Hui-Ming Cheng: Faculty of Materials Science and Engineering / Institute of Technology for Carbon Neutrality, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: Abstract Materials capable of extracting gold from complex sources, especially electronic waste (e-waste), are needed for gold resource sustainability and effective e-waste recycling. However, it remains challenging to achieve high extraction capacity and precise selectivity if only a trace amount of gold is present along with other metallic elements . Here we report an approach based on reduced graphene oxide (rGO) which provides an ultrahigh capacity and selective extraction of gold ions present in ppm concentrations (>1000 mg of gold per gram of rGO at 1 ppm). The excellent gold extraction performance is accounted to the graphene areas and oxidized regions of rGO. The graphene areas spontaneously reduce gold ions to metallic gold, and the oxidized regions allow good dispersibility of the rGO material so that efficient adsorption and reduction of gold ions at the graphene areas can be realized. By controlling the protonation of the oxidized regions of rGO, gold can be extracted exclusively, without contamination by the other 14 co-existing elements typically present in e-waste. These findings are further exploited to demonstrate recycling gold from real-world e-waste with good scalability and economic viability, as exemplified by using rGO membranes in a continuous flow-through process.

Date: 2022
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DOI: 10.1038/s41467-022-32204-4

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