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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

Postal Subscription Code 80-973

2018 Impact Factor: 3.883

Front. Environ. Sci. Eng.    2023, Vol. 17 Issue (10) : 123    https://doi.org/10.1007/s11783-023-1723-z
RESEARCH ARTICLE
Non-toxic, high selectivity process for the extraction of precious metals from waste printed circuit boards
Giulia Merli, Alessandro Becci(), Alessia Amato, Francesca Beolchini
Department of Life and Environmental Sciences, Polytechnic University of Marche, Ancona 60131, Italy
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Abstract

● Au, Ag and Pd were recovered from WPCBs with high efficiencies.

● Au leaching is strictly dependent on WPCB size and reagent concentration.

● High Ag extraction efficiencies are achieved regardless of the WPCB size.

● Pd leaching works better with small and medium WPCB sizes.

● The leaching results suggest the possibility of selective recovery of metals.

The work presented here focused on the extraction of gold (Au), silver (Ag) and palladium (Pd) from electronic waste using a solution of ammonium thiosulfate. Thiosulfate was used as a valid alternative to cyanide for precious metal extractions, due to its non-toxicity and high selectivity. The interactions between sodium thiosulfate, total ammonia/ammonium, precious metal concentrations and the particle size of the waste printed circuit boards (WPCBs) were studied by the response surface methodology (RSM) and the principal component analysis (PCA) to maximize precious metal mobilization. Au extraction reached a high efficiency with a granulometry of less than 0.25 mm, but the consumption of reagents was high. On the other hand, Ag extraction depended neither on thiosulfate/ammonia concentration nor granulometry of WPCBs and it showed efficiency of 90% also with the biggest particle size (0.50 < Ø < 1.00 mm). Pd extraction, similarly to Au, showed the best efficiency with the smallest and the medium WPCB sizes, but required less reagents compared to Au. The results showed that precious metal leaching is a complex process (mainly for Au, which requires more severe conditions in order to achieve high extraction efficiencies) correlated with reagent concentrations, precious metal concentrations and WPCB particle sizes. These results have great potentiality, suggesting the possibility of a more selective recovery of precious metals based on the different granulometry of the WPCBs. Furthermore, the high extraction efficiencies obtained for all the metals bode well in the perspective of large-scale applications.

Keywords Thiosulfate      Printed circuit boards      Precious metals      Leaching      Hydrometallurgy     
Corresponding Author(s): Alessandro Becci   
About author:

*These authors equally shared correspondence to this manuscript.

Issue Date: 28 April 2023
 Cite this article:   
Giulia Merli,Alessandro Becci,Alessia Amato, et al. Non-toxic, high selectivity process for the extraction of precious metals from waste printed circuit boards[J]. Front. Environ. Sci. Eng., 2023, 17(10): 123.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-023-1723-z
https://academic.hep.com.cn/fese/EN/Y2023/V17/I10/123
Fig.1  WPCBs with different granulometries: lower than 0.10 < ? < 0.25 mm (a), 0.25 < ? < 0.50 mm (b) and 0.50 < ? < 1.00 mm (c) tested by SEM analysis.
CodeFactors?10+ 1
X1[Ammonia/ammonium] (mol/L)0.20.61
X2[Thiosulfate] (mol/L)0.10.551
X3Granulometry (mm)0.1 < ? < 0.250.25 < ? < 0.500.50 < ? < 1.00
Tab.1  Factors and levels for the CCD-RSM
Fig.2  Au dissolution in the final liquor with small size WPCBs (0.10 < ? < 0.25 mm, in green): ● 0.2 mol/L NH3 0.1 mol/L thiosulfate, ■ 1 mol/L NH3 0.1 mol/L thiosulfate, ? 0.2 mol/L NH3 1 mol/L thiosulfate, ▲ 1 mol/L NH3 1 mol/L thiosulfate; big size WPCBs (0.50 < ? < 1.00 mm, in pink): ● 0.2 mol/L NH3 0.1 mol/L thiosulfate, ■ 1 mol/L NH3 0.1 mol/L thiosulfate, ? 0.2 mol/L NH3 1 mol/L thiosulfate, ▲ 1 mol/L NH3 1 mol/L thiosulfate; and medium size (0.25 < ? < 0.50 mm, in black): * 0.6 mol/L ammonia/ammonium 0.55 mol/L thiosulfate.
Fig.3  Simulated data vs. real data for Au mobilization.
SourcesSum of squaresdfMean squareF-valuep-value
Linear (X1, X2, X3, X4)47466264118665615.67****
Interaction (X1, X2, X3, X4)233580663893015.14**
Quadratic (X3, X4)146748027337409.69***
Residual19685072675712
Lack of fit1957804228899133.26**
Pure error1070342676
Tab.2  Summary of ANOVA results for RSM for Au mobilization
Fig.4  Contours of thiosulfate vs. ammonium (a) and time vs. granulometry (b) for Au mobilization.
Fig.5  Ag dissolution in the final liquor with small size WPCBs (0.10 < ? < 0.25 mm, in green): ● 0.2 mol/L NH3 0.1 mol/L thiosulfate, ■ 1 mol/L NH3 0.1 mol/L thiosulfate, ? 0.2 mol/L NH3 1 mol/L thiosulfate, ▲ 1 mol/L NH3 1 mol/L thiosulfate; big size WPCBs (0.50 < ? < 1.00 mm, in pink): ● 0.2 mol/L NH3 0.1 mol/L thiosulfate, ■ 1 mol/L NH3 0.1 mol/L thiosulfate, ? 0.2 mol/L NH3 1 mol/L thiosulfate, ▲ 1 mol/L NH3 1 mol/L thiosulfate; and medium size (0.25 < ? < 0.50 mm, in black): * 0.6 mol/L ammonia/ammonium 0.55 mol/L thiosulfate.
Fig.6  Simulated data vs. real data for Ag mobilization.
SourcesSum of squaresdfMean squareF-valuep-value
Linear (X1, X2, X3, X4)551305110413782627760.98****
Interaction (X1, X2, X3, X4)12257716620429530.900.51
Quadratic (X3, X4)18972817229486408641.97****
Residual58764834262260186
Lack of fit573809762226082267.54*
Pure error13838584345964
Tab.3  Summary of ANOVA results for RSM for Ag mobilization
Fig.7  Contours of thiosulfate vs. ammonium (a) and time vs granulometry (b) for Ag mobilization.
Fig.8  Pd dissolution in the final liquor with small size WPCBs (0.10 < ? < 0.25 mm, in green): ● 0.2 mol/L NH3 0.1 mol/L thiosulfate, ■ 1 mol/L NH3 0.1 mol/L thiosulfate, ? 0.2 mol/L NH3 1 mol/L thiosulfate, ▲ 1 mol/L NH3 1 mol/L thiosulfate; big size WPCBs (0.50 < ? < 1.00 mm, in pink): ● 0.2 mol/L NH3 0.1 mol/L thiosulfate, ■ 1 mol/L NH3 0.1 mol/L thiosulfate, ? 0.2 mol/L NH3 1 mol/L thiosulfate, ▲ 1 mol/L NH3 1 mol/L thiosulfate; and medium size (0.25 < ? < 0.50 mm, in black): * 0.6 mol/L ammonia/ammonium 0.55 mol/L thiosulfate.
SourcesSum of squaresdfMean squareF-valuep-value
Linear (X1, X2, X3, X4)919234422980922.63****
Interaction (X1, X2, X3, X4)1032546172091.690.16
Quadratic (X3, X4)1637322818668.06**
Residual2640712610157
Lack of fit22856222103891.170.49
Pure error3550948877
Tab.4  Summary of ANOVA results for RSM for Pd mobilization
Fig.9  Simulated data vs. real data for Pd mobilization.
Fig.10  Contours of thiosulfate vs. ammonium (a) and time vs. granulometry (b) for Pd mobilization.
MetalGranulometry
0.10 < ? < 0.25 mm0.25 < ? < 0.50 mm0.50 < ? < 1.00 mm
MeanSt.dev.MeanSt.dev.MeanSt.dev.
Au170± 30212± 61100± 200
Ag1690± 50220± 3400± 100
Pd42± 432± 830± 6
Tab.5  Metal concentrations in the different particle sizes (mg/kg)
Fig.11  Changing in the molar ratio between thiosulfate (a) or ammonia (b) and the precious metal concentrations in the different experimental plans.
Fig.12  Principal component analysis (PCA) results.
Fig.13  Au, Ag and Pd extraction efficiencies (%) in the different experiments.
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