Copper is the main component of printed circuit boards (PCBs) which is the main part of an electronic device. The manufacture of PCBs often releases huge amount of sludge which contained copper. Derived from the demand of the industrial park about the wasted sludge treatment and the reducing of the plantation of natural mineral resources, the copper recovery process from PCBs manufacture's wasted sludge was studied. The process of copper leaching by sulfuric acid solution was studied using experimental planning methods using the simulation software Modde 5.0. The parameters were calculated and simulated to evaluate the effect of the acid concentration, leaching time, and the ratio between the solid and liquid phases on the leaching efficiency. The obtained results by simulation were compared with real experimental results. The obtained results from this study are planning in the actual deployment of the Hanoi Urban Environment One Member Limited Company in Vietnam. Keywords. Printed circuit board, copper sludge, leaching

Bich Thuy, Hoang Thi

Binh Thanh, Nguyen Dang

Dung, Dang Trung

Giang, Nguyen Huong

Thu Huyen, Nguyen Thi

Tung, Mai Thanh

Vietnam Academy of Science and Technology: Journals Online

 Vietnam Journal of Chemistry, International Edition, 55(2): 254-258, 2017 
DOI: 10.15625/2525-2321.2017-00455 
254 
 
 
 
Optimization of the leaching process of the printed circuit boards 
production's sludge for copper recovery via electrolysis 
Nguyen Thi Thu Huyen
*
, Dang Trung Dung, Nguyen Huong Giang, Nguyen Dang Binh Thanh,        
Mai Thanh Tung, Hoang Thi Bich Thuy
 
School of Chemical Engineering, Hanoi University of Science and Technology 
Received 1 August 2016; Accepted for publication 11 April 2017 
 
Abstract 
Copper is the main component of printed circuit boards (PCBs) which is the main part of an electronic device. The 
manufacture of PCBs often releases huge amount of sludge which contained copper. Derived from the demand of the 
industrial park about the wasted sludge treatment and the reducing of the plantation of natural mineral resources, the 
copper recovery process from PCBs manufacture's wasted sludge was studied. The process of copper leaching by 
sulfuric acid solution was studied using experimental planning methods using the simulation software Modde 5.0. The 
parameters were calculated and simulated to evaluate the effect of the acid concentration, leaching time, and the ratio 
between the solid and liquid phases on the leaching efficiency. The obtained results by simulation were compared with 
real experimental results. The obtained results from this study are planning in the actual deployment of the Hanoi Urban 
Environment One Member Limited Company in Vietnam. 
Keywords. Printed circuit board, copper sludge, leaching. 
 
1. INTRODUCTION 
 
The production of electronic equipment is 
rapidly increasing in the world as a result of the 
revolution of information technology. Consequently, 
waste electronic equipment is a growing concern 
globally. Printed circuit boards (PCBs) are used in 
almost all electronics today and fabricated in large 
volumes across the world. The increasing volume of 
waste discharges from PCBs manufacture poses an 
environmental threat, as this sludge can contain 
substances that are harmful, such as heavy metals, 
nitrates and phosphates. Copper is one of the most 
used materials in the production of PCBs [1]. The 
copper recovery from sludge of the PCBs production 
became more important lately because of the 
continuous increase of copper demand, as well as the 
urgent in solving the environmental issues. 
One of the big challenges for copper recovery 
via hydrometallurgy from copper sludge is how to 
form a concentrated copper ion solution and 
leaching is a popular method to solve this problem. 
There are some different leaching techniques such as 
bio-leaching, heap leaching, oxidized leaching, 
pressure leaching, and also, leaching process can be 
done using acid or base solutions. Although there are 
some disadvantages, especially the separation of 
copper from the other metal contaminants but acid 
leaching process is still preferred for low-grade ores 
and solid waste treatment because of the high 
leaching efficiency. Nitric acid and hydrochloric 
acid can dissolve low-grade ore or e-waste easily but 
because of the bad effect of Cl-, and NO3
- anions to 
the next step - electrodeposition, these acids are not 
normally used in the real industrial techniques [2,3]. 
Therefore, cause of the conformity of the copper 
sulphate solution for electrowinning, the leaching 
process using sulphuric acid has widely been used 
for the copper recovery from low-grade complex 
ores [4, 5] or industrial wastes [6]. 
In this paper, the leaching process of the copper 
sludge from PCBs production has been carried out 
using statistical design of experiments for different 
process parameters. The real experiment's and 
simulation' results were compared. The response 
surface modeling has been performed to optimize 
the best conditions for leaching of copper from the 
sludge by using Modde 5.0 software on a personal 
computer. 
 
2. EXPERIMENTAL 
 
2.1. Materials and reagents 
  
PCBs wastes used in this study were sourced 
from Hanoi Urban Environment One Member 
 VJC, 55(2), 2017  Nguyen Thi Thu Huyen et al. 
255 
Limited Company (Urenco). The desiccate PCBs 
sludge was grinded and sieved to achieve the size 
smaller than 0.1mm. Analytical grade sulfuric acid 
was used in the experiments. The leach solutions 
were prepared by dissolving the desired volume of 
sulfuric acid in deionized water to the required 
concentration. 
 
2.2. Leaching process 
  
 The experiments were conducted at room 
temperature in a 0.5 L glass beaker, using a 
magnetic stirrer rotating at a speed of 600 rpm. In 
each experiment, a quantity of 100 mL sulfuric acid 
was introduced into the reactor. When the desired 
stirring speed was reached, the solid sample was 
added into the reactor. The amount of solid sample 
was changed to satisfy the ratio of solid/liquid. After 
specific time intervals, the leaching solutions were 
filtered. The copper concentration in the filtrate was 
determined using UV-Vis spectrophotometry at the 
wavelength of 805 nm. The leaching efficiency was 
calculated based on the copper concentration in the 
sample before and after leaching. 
 
2.3. Modeling and Simulation 
  
Method of modeling and statistical design of 
experiments on quadratic central composite design 
(CCD) improved by Box and Hunter [7] was used to 
model the surface response in this study. The 
leaching efficiency was taken as the response 
variable, where the concentration of sulfuric acid 
(X1, M), time of leaching (X2, min) and the ratio of 
solid/liquid (X3, %) were considered as the 
independent variables (factors). The relationship 
between the coded values and the experimental 
values was described by the following Eq. (1). 
                           
(1)
 
where xj, Zj are the coded and the experimental value 
of the independent variable respectively,  is the 
experimental value of the independent variable at the 
center point level, and ΔZj is the step change of 
variable.  
Table 1: Central composite rotatable design 
arrangement and results 
Run 
Independent variable 
Eff. [H2SO4] 
(M) 
Leaching 
time 
(min) 
The ratio 
of S/L 
(%) 
1 0.8 30 10 0.77 
2 1.2 30 10 0.91 
3 0.8 90 10 0.80 
4 1.2 90 10 0.95 
5 0.8 30 14 0.75 
6 1.2 30 14 0.81 
7 0.8 90 14 0.78 
8 1.2 90 14 0.88 
9 0.66 60 12 0.66 
10 1.34 60 12 0.85 
11 1.0 9.54 12 0.89 
12 1.0 110.46 12 0.96 
13 1.0 60 8.36 0.88 
14 1.0 60 15.36 0.79 
15 1.0 60 12 0.96 
16 1.0 60 12 0.95 
17 1.0 60 12 0.93 
18 1.0 60 12 0.94 
19 1.0 60 12 0.93 
20 1.0 60 12 0.95 
 
Table 1 shows the total number of required 
experimental runs and the levels in coded and actual 
value of the acid concentration. The leaching time 
and solid/liquid ration were shown in table 2. 
  Table 2: Independent variables and their corresponding levels 
Independent 
variables 
Symbol 
code 
Code variable levels 
-1.682 -1 0 1 1.682 
Sulfuric acid 
concentration (M) 
Z1 0.6636 0.8 1.0 1.2 1.3364 
Time of leaching  
(min) 
Z2 9.54 30 60 90 110.46 
The ratio of solid/ 
liquid (%) 
Z3 8.36 10 12 14 115.36 
 
The results of 20 trials were also entered into the 
Modde 5.0 software in order to fit the model by 
multiple linear regressions. The previous 
investigation indicates that the best-fit model of 
x j =
Z j - Z j
0
DZ j
 VJC, 55(2), 2017  Optimization of the leaching process of… 
256 
response Y is quadratic model. This model is given 
by the general expression: 
 
where Y is copper leaching efficiency, Xi, Xj, are the 
coded values of independent variables, the terms 
XiXj and Xi
2 represent the interaction and quadratic 
terms, respectively, b0 is the constant coefficient, bi, 
bii, and bij namely the linear, quadratic and 
interaction coefficient. 
 
3. RESULTS AND DISCUSSION 
 
3.1. Modeling of copper leaching efficiency 
  
Table 3 shows the estimated regression 
coefficients for the leaching efficiency model. The 
confidence level of model was 95 %. The model was 
then verified by checking the Student's t-
distribution. At the confidence level P = 0.05, the 
coefficients b22, b21, b23 did not satisfy and hence 
they were rejected.  The accuracy and variability of 
the above model could also be evaluated by the 
coefficient of determination (R2). The R2 for the 
copper leaching efficiency was calculated to be 
0.971, explaining that the variability of response is 
at 97.1 % confidence level, and only 2.9 % of the 
total variations cannot be explained by the model. 
Moreover, the value of adjusted determination 
coefficient (adj. R2) of 0.945 was also close to 1. 
Therefore, the predicted model for copper leaching 
efficiency had a good agreement with the 
experimental data.  
 
 
 
Figure 1: Linear correlation between observed and 
predicted values for copper leaching 
Final regression equation for the copper leaching 
efficiency, which incorporates the types of coded 
coefficients, is shown in Eq. (2): 
Y = 0.943 + 0.064X1 + 0.020X2 - 0.044X3 -0.070X1
2 
 
- 0.042X3
2 - 0.034X1.X3                                          (2)                                     
 
The model equation indicates that the copper 
leaching efficiency involves the second and no 
higher order of sulfuric acid concentration and ratio 
of solid/liquid. Figure 1 shows plot of the predicted 
vs. experimental value for copper leaching 
efficiency. It could be seen that the experimental 
results were distributed relatively near to a straight 
line, which confirms the good agreement between 
the predicted and actual results. This illustrates that 
the fitted regression coefficient to the equation and 
the CCD model with an experimental design can be 
effectively applied for optimization of copper 
leaching efficiency. 
 
Table 3: Estimated regression coefficients for 
quadratic model 
Source Coefficient Standard error P 
Model 0.943 0.001 <0.001 
X1 0.064 0.006 <0.001 
X2 0.020 0.006 0.012 
X3 -0.004 0.006 <0.001 
 -0.070 0.006 <0.001 
 -0.014 0.006 0.054 
 -0.042 0.006 <0.001 
X1X2 -0.006 0.008 0.454 
X1X3 0.034 0.008 0.002 
X2X3 0.014 0.008 0.132 
 
3.2. The interaction among factors and its effect 
on copper leaching efficiency 
  
Figures 2, 3 and 4 illustrate the interaction 
among process factors and their effect on copper 
leaching efficiency. 
It can be seen from figure 2 that the shape of the 
plot was almost uniform when the ratio of 
solid/liquid and the time of leaching were changed 
simultaneously. A similar trend was also recorded in 
figures 3 and 4. This seems to be confirmed that the 
interaction between each pair of factor is completely 
independent. 
 VJC, 55(2), 2017  Nguyen Thi Thu Huyen et al. 
257 
 
Figure 2: Effect of sulfuric acid concentration and 
the ratio of solid/liquid on leaching efficiency 
 
 
Figure 3: Effect of the leaching time and the ratio of 
solid/liquid on leaching efficiency 
 
 
Figure 4: Effect of sulfuric acid concentration and 
the leaching time on leaching efficiency 
3.3. Optimization of copper leaching conditions 
  
In order to find the optimum conditions of 
copper leaching with the highest efficiency, the 
lowest consumption of materials and time is stressed 
upon this investigation. The response surface 
methodology (RSM) can be used to find desirable 
location in the design space. While using the RSM 
with the help of Modde 5.0 software the best 
conditions of copper leaching process were 
determined. Table 4 demonstrated the results of the 
process optimization and optimum levels of 
variables.  
Table 4: Results of process optimization and 
optimum levels of variables 
Proposed 
range 
[H2SO4] (M) 0.8-1.2 
Time (min) 30-90 
Ratio of S/L (%) 10-14 
Target Maximum 
Optimum 
values of 
variables 
[H2SO4] (M) 1.08 
Time (min) 75.15 
Ratio of S/L (%) 12.59 
Leaching efficiency (%) 96.67 
 
The optimum conditions have been found as: 
sulfuric acid concentration of 1.08 M, leaching time 
of 75.15 minute, the ratio of solid/liquid of 12.59 %. 
Under these conditions, the leaching efficiency 
reached 96.67 %.  
 
4. CONCLUSION 
  
A quadratic model of copper leaching efficiency 
has been obtained by using RSM based on CCD 
with the help of Modde 5.0 software. A good 
agreement between model and experiment is 
confirmed. The final quadratic model was used to 
find the optimum conditions for copper leaching, 
which turn out as sulfuric acid concentration of 1.08 
M, leaching time of 75.15 minute, the ratio of 
solid/liquid of 12.59 %. Maximum value of copper 
leaching efficiency under optimum conditions was 
calculated to be 96.67 %. 
 
Acknowledgement. Newton Fund of England - 
Advanced Electrochemical Method for Treatment 
and Metal Recycling of Industrial Solid Waste 
project, funded this paper.  
 VJC, 55(2), 2017  Optimization of the leaching process of… 
258 
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Corresponding author:  Nguyen Thi Thu Huyen  
Department of Electrochemical and Corrosion protection 
Hanoi University of Science and Technology  
No 1, Dai Co Viet, Hai Ba Trung District, Hanoi 
E-mail: huyen.nguyenthithu@hust.edu.vn; Telephone number: 0916833409. 


Optimization of the leaching process of the printed circuit boards production’s sludge for copper recovery via electrolysis

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