Arsenic removal from arsenic-containing copper and cobalt slag using alkaline leaching technology and MgNH4AsO4 precipitation
Arsenic removal from arsenic-containing copper and cobalt slag using alkaline leaching technology and MgNH4AsO4 precipitation
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碱浸技术和MgNH4AsO4沉淀法从含砷铜钴渣中脱砷
DOI:
10.1016/j.seppur.2019.116422
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发表时间:
2020-05
影响因子:
8.6
通讯作者:
Tang Honghu
中科院分区:
文献类型:
--
作者:
Zhang Xingfei;Tian Jia;Han Haisheng;Sun Wei;Hu Yuehua;Wang Tong Yue Li;Yang Yue;Cao Xuefeng;Tang Honghu
In this study, a novel alkaline cycle leaching and MgNH4AsO4precipitation technology was used to remove arsenic in arsenic–containing copper and cobalt slag. The phase analysis results indicated the arsenic species mostly existed in the original slag as Cu-As alloy. By adopting NaOH-H2O2leaching method, the arsenic leaching reached as high as 94.5% under the optimum conditions. The XRD results indicated that copper in the Cu-As alloy was oxidized to be Cu(OH)2in high concentration NaOH solution. And the optimum conditions were established as: NaOH concentration, 2 mol/L; leaching temperature, 25℃; H2O2concentration, 5%; and liquid-solid ratio (L/S), 9:1. Thermodynamic analysis showed that it was feasible to selectively precipitate arsenate in alkaline leaching solution in the form of MgNH4AsO4. The XRD results confirmed that the arsenic in the filter residue mainly existed in the form of MgNH4AsO4·6H2O, which has good crystallinity, contributing to a better arsenic and alkali separation. Under the optimum conditions, the content of arsenic in the purified liquid and purified residue were 39 mg/L and 24.15%, respectively. Thus, the purified alkaline solution could be circulated for the leaching process, which is beneficial to the cost reduction and environment protection.
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DOI:
10.2473/shigentosozai.116.779
发表时间:
2000
期刊:
Shigen-to-sozai
影响因子:
--
作者:
T. Ohgai;H. Fukushima;T. Akiyama;S. Heguri
通讯作者:
T. Ohgai;H. Fukushima;T. Akiyama;S. Heguri
影响因子:
11.4
作者:
Bothe, JV;Brown, PW
通讯作者:
Brown, PW
影响因子:
8.6
作者:
Gu, Kunhong;Li, Wenhua;Cai, Lianbing
通讯作者:
Cai, Lianbing
影响因子:
4.8
作者:
Awe, Samuel A.;Sandstrom, Ake
通讯作者:
Sandstrom, Ake
影响因子:
8.7
作者:
Channratha Prum;R. Dolphen;P. Thiravetyan
通讯作者:
Channratha Prum;R. Dolphen;P. Thiravetyan