Box-Wilson experimental design for electroless copper

International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 –
6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME
46
APPLICATION OF BOX-WILSON EXPERIMENTAL DESIGN METHOD
FOR ELECTROLESS COPPER PLATING
Hameed Hussein Alwan
Electrochemical Engineering Dept. / College of Engineering / Babylon University /Iraq
ABSTRACT
In this study, electroless copper plating was done by used Box-wilson experimental design as
experimental design method to find the effect of most controllable variables on electroless copper
plating process. To study these effect four variables were considered as most dominate variables.
These variable are; Formalin concentration in rang 0.05-0.30 M, CuSO4 concentration in rang
0.005-0.045 M, temperature in rang 30-70 ° C and, pH solution in rang 11-13. These four variables
are manipulated through experimental work by using Box-wilson experimental design by proposed
second order polynomial model to correlate the studied effect of these variables on deposited copper
layer thickness. The predicated models are found after analyzing statistically as follows:
222.0
369.0215.0306.0188.1207.1392.0663.0516.4
2
4
2
3
2
2
2
14321
X
XXXXXXXy
+
+−−++++=
Where y is the deposited copper layer thickness, X1 formalin concentration, X2 CuSO4
concentration , X3 temperature and , X4 solution pH .
The study shows that formalin and CuSO4 concentrations have great significance effect on
the deposited copper layer thickness while the temperature and pH solution have small dependence
on layer thickness.
Optimum conditions for getting the maximum deposited copper layer thickness are obtained
by using optimization method on the above model.
Keywords: Electroless Plating, Copper, Box-Wilson Experimental Design.
INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING
AND TECHNOLOGY (IJARET)
ISSN 0976 - 6480 (Print)
ISSN 0976 - 6499 (Online)
Volume 5, Issue 4, April (2014), pp. 46-56
© IAEME: www.iaeme.com/ijaret.asp
Journal Impact Factor (2014): 7.8273 (Calculated by GISI)
www.jifactor.com
IJARET
© I A E M E

47
INTRODUCTION
Electroless deposition of metals and alloys has a very significant practical importance in
modern technology especially in the production of new materials for applications in electronics, wear
and corrosion resistant materials, medical devices, battery technologies, etc.
All solutions for electroless metal deposition have many similarities, but depending on the
metal or alloy to be deposited, there are also some differences. Typically, the constituents of a
solution for electroless metal deposition are; source of metal ions, complexing agent, reducing
agents, stabilized and inhibitor i.e.electroless copper deposition, CuSo4 is used mainly as the source
of copper ions. [1]
Electroless plating is a wet chemical plating technique utilized by semiconductor industry to
deposit thin films of metal or metal alloy over a substrate during fabrication or packaging of
semiconductor devices. Electroless plating can be accomplished with relatively low cost tooling and
materials as compared to electroplating. Further, Electroless plating is selective, provides excellent
step coverage and good filling capabilities. [2]
Electroless copper plating involves the reduction of copper ions to copper metal from
solution contain copper ions i.e. CuSO4 and the surface catalyzed oxidation of a reducing agent.
These processes are widely used in the fabrication of printed circuit boards due to their conformal
deposition, low cost, and simple equipmental setup. Commercial electroless copper plating solutions
often use formaldehyde or its derivatives as reducing agents because of their high deposition rate and
the excellent mechanical properties of the copper deposits [1]. The complexing agent such as
ethylene diaminetetra acetic acid EDTA, a reducing agent such as formalin and pH adjusting agent
such as alkali hydroxide as main components. [3]
The solution pH is a very important factor in the electroless deposition, indeed, it affects both
anodic and cathodic reactions and various phenomena associated with the structure and composition
of the metal-solution interphase. The plating rate increases remarkably when the solution pH
increases[4]. MichinariSone et.al show that deposition rate increased with an increase in pH, fine
copper particles were generated, and the stability of the bath decreased at a pH greater than 6.5. As
the bath temperature increased, the deposition rate increased up to 50 ◦C, but particles were formed
in the bath. [5]
In this study, the Box-Wilson experimental design method was used in order to investigate
the effects of important controllable variables on copper electroless plating. The experimental design
is a response surface methodology used to evolution the dependent variable (thickness of copper
deposited) as a function of independent variables (CuSO4 concentration, Formalin concentration, pH
solution and Temperature). Optimum conditions for achieving the maximum film thickness
deposited are obtain from optimizing the correlation.
EXPERIMENTAL WORK
Material
Carbon steel (200 mm long x 50 mm wide x 2 mm thickness) as a substrate plate.
Chemicals
CuSO4 as a copper ions source, Formalin as reducing agent, EDTA as complexing agent and
NaOH for pH adjusting.
Procedure
The substrate was mechanically polished down 1200 by emerypaper, dipped into 5% NaOH
solution at 60 ӷ C for 5 minutes, rinsed with water and dipped in 15% HCl solution at room

48
temperature for 2 minutes and, after that the substrate was dipped in the electroless plating solution
(CuSO4, Formalin, EDTA and NaOH) the solution composition was prepare according to the
experiment design. The substrate was weighted before and after immersion in a solution, the solution
temperature was adjusted to desired value and for required time.
The thickness of copper deposited thickness calculated by below equation:
(1)
10)( 4
21
ρS
WW
Y
×−
=
Where Y= coating thickness in micron (µm).
W1 = weight of a specimen before impressed in solution in gram
W2 = weight of a specimen after impressed in solution in gram.
S = surface area in dm2
.
ρ = density in g / cm3
Box-wilson experiment design
Box-wilson design is a response surface methodology RSM, and empirical modeling
technique, devoted to the evaluation of relationship of a set of controlled experimental factors and
observed results, the optimization process involves three step ;statistical design experiment , estimate
coefficient for mathematical model , and predicting the response [6].
Response surface methodology or (RSM) is a collection of mathematical and statistical
techniques useful for analyzing problems where several independent variables influence a dependent
variable or response, and the goal is to optimize this response X1, X2 …. And Xq denote the
independent variable that are continues and controllable by the experimenter with negligible error.
[7-8]
The operating parameters: concentration of reduction agent formalin (X1), copper ion
concentration (X2), operating temperature (X3), and solution pH (X4). The response is the thickness
of copper deposited layer (y).For four variables the quadratic polynomial equation can be represented
as follows:
(3)
(2)
43144213321241113110219
2
48
2
37
2
26
2
1544332211
2
11
XXbXXbXXbXXbXXbXXb
XbXbXbXbXbXbXbXbby
XXbXbXbby jii
q
jii
q
iii
q
i
+++++
++++++++=∴
+∑+∑+= ∑ ∑==
o
o
Where y is the predicated copper layer thickness (µm)
b0 constant ,
b1, b2, b3 and, b4 linear coefficients,
b5, b6, b7 and b8 quadratic coefficients,
b9 , b10, b11, b12, b13 and, b14 cross-product coefficients.
q, number of variables and in this case are q = 4.

49
A preliminary step is to set up between coded level and the corresponding real variables
which are required to determine the experimental range by the following equation:
(4)
min
q
XX
XX
X
cen
cenreal
coded
−
−
=
The number of experimental run required to cover range for four variables in this case.
(6)284422
(5)422
4
=+×+=
++=
N
qN q
The coded variables tae values between -2 and 2, and according to these values the range of
real variables for the system can be represented in tables(1) and (2).
Table (1): The experimental range of variables
Reduction agent
concentration (M)
Copper sulfate
concentration (M)
Temperature
(° C)
pH
0.05-0.3 0.005-0.045 30-70 11-13
Table (2): Relationship between coded and real variables
Variables Levels
X1,X2,X3, X4 -2 -1 0 1 2
X1=Reduction agent concentration (M) 0.05 0.1125 0.175 0.2375 0.3
X2=Copper sulfate concentration (M) 0.005 0.015 0.025 0.035 0.045
X3=Temperature(° C) 30 40 50 60 70
X4=pH 11 11.5 12 12.5 13

50
Table (3): experimental design condition according to a Box-Wilson experiment design with four
independent variables
coded real
x1 x2 x3 x4
Formalin
Conc. M
CuSO4
Conc. M
Temp.
° C
pH
1 -1 -1 -1 -1 0.1125 0.015 40 11.5
2 1 -1 -1 -1 0.2375 0.015 40 11.5
3 -1 1 -1 -1 0.1125 0.035 40 11.5
4 1 1 -1 -1 0.2375 0.035 40 11.5
5 -1 -1 1 -1 0.1125 0.015 60 11.5
6 1 -1 1 -1 0.2375 0.015 60 11.5
7 -1 1 1 -1 0.1125 0.035 60 11.5
8 1 1 1 -1 0.2375 0.035 60 11.5
9 -1 -1 -1 1 0.1125 0.015 40 12.5
10 1 -1 -1 1 0.2375 0.015 40 12.5
11 -1 1 -1 1 0.1125 0.035 40 12.5
12 1 1 -1 1 0.2375 0.035 40 12.5
13 -1 -1 1 1 0.1125 0.015 60 12.5
14 1 -1 1 1 0.2375 0.015 60 12.5
15 -1 1 1 1 0.1125 0.035 60 12.5
16 1 1 1 1 0.2375 0.035 60 12.5
17 -2 0 0 0 0.05 0.025 50 12
18 2 0 0 0 0.3 0.025 50 12
19 0 -2 0 0 0.175 0.005 50 12
20 0 2 0 0 0.175 0.045 50 12
21 0 0 -2 0 0.175 0.025 30 12
22 0 0 2 0 0.175 0.025 70 12
23 0 0 0 -2 0.175 0.025 50 11
24 0 0 0 2 0.175 0.025 50 13
25 0 0 0 0 0.175 0.025 50 12
26 0 0 0 0 0.175 0.025 50 12
27 0 0 0 0 0.175 0.025 50 12
28 0 0 0 0 0.175 0.025 50 12
RESULTS AND DISCUSSION
Table 4- shows the experimental data (observed practically) and predicated (Calculated by
software) values of the thickness of copper layer plated, the experimental results were modeled using
a STATISTIC software Ver.5.5A, regression analysis to determine the coefficients of response
model (equation 3). The calculated coefficients listed in table 5. The determination coefficient
between the observed and predicated values was estimated of second order polynomial regression by
using, the number of iterations was terminated when the proportion of variance accounted for was
(99.87%) and the correlation factor R was equal (0.99937).

51
Table (4): Experimental data and predicated values of the thickness of copper layer plated
coded real
Observed
Experimenta
l Thickness
Y.
Predicted
thickness
y
Residual
Ei=Y-yx1 x2 x3 x4
Formalin
concentratio
n (M)
Copper
sulfate
concentratio
n (M)
Temp.
ͦ C
pH
1 -1 -1 -1 -1 0.1125 0.015 40 11.5 1.14 1.225 -0.085
2 1 -1 -1 -1 0.2375 0.015 40 11.5 2.46 2.259 0.201
3 -1 1 -1 -1 0.1125 0.035 40 11.5 1.92 1.808 0.112
4 1 1 -1 -1 0.2375 0.035 40 11.5 3.25 2.934 0.316
5 -1 -1 1 -1 0.1125 0.015 60 11.5 3.55 3.746 -0.196
6 1 -1 1 -1 0.2375 0.015 60 11.5 4.88 4.860 0.020
7 -1 1 1 -1 0.1125 0.035 60 11.5 4.33 4.373 -0.043
8 1 1 1 -1 0.2375 0.035 60 11.5 5.66 5.579 0.081
9 -1 -1 -1 1 0.1125 0.015 40 12.5 3.52 3.449 0.071
10 1 -1 -1 1 0.2375 0.015 40 12.5 4.84 4.883 -0.043
11 -1 1 -1 1 0.1125 0.035 40 12.5 4.3 4.287 0.013
12 1 1 -1 1 0.2375 0.035 40 12.5 5.62 5.814 -0.194
13 -1 -1 1 1 0.1125 0.015 60 12.5 5.93 5.636 0.294
14 1 -1 1 1 0.2375 0.015 60 12.5 7.25 7.150 0.100
15 -1 1 1 1 0.1125 0.035 60 12.5 6.71 6.519 0.191
16 1 1 1 1 0.2375 0.035 60 12.5 8.04 8.125 -0.085
17 -2 0 0 0 0.05 0.025 50 12 1.96 2.120 -0.160
18 2 0 0 0 0.3 0.025 50 12 4.62 4.760 -0.140
19 0 -2 0 0 0.175 0.005 50 12 2.87 3.003 -0.133
20 0 2 0 0 0.175 0.045 50 12 4.44 4.561 -0.121
21 0 0 -2 0 0.175 0.025 30 12 3.58 3.630 -0.050
22 0 0 2 0 0.175 0.025 70 12 8.41 8.462 -0.052
23 0 0 0 -2 0.175 0.025 50 11 3.03 2.509 0.521
24 0 0 0 2 0.175 0.025 50 13 7.78 7.279 0.501
25 0 0 0 0 0.175 0.025 50 12 4.52 4.796 -0.276
26 0 0 0 0 0.175 0.025 50 12 4.555 4.796 -0.241
27 0 0 0 0 0.175 0.025 50 12 4.735 4.796 -0.061
28 0 0 0 0 0.175 0.025 50 12 4.255 4.796 -0.541

52
Table 5: Coefficients for the response function
Coefficient. B0 B1 B2 B3 B4 B5 B6 B7
Value 4.51637 0.66333 0.39168 1.20663 1.18830 -0.30639
-
0.21515
0.36986
Coefficient. B8 B9 B10 B11 B12 B13 B14
Value 0.22235 0.00123 0.00123 -0.00127 -0.00002 -0.00002
-
0.00002
Correlation Coefficient R 0.99937 Variance explained % 99.87%
Correlation the four variables with deposited copper layer thickness, the following response
was obtained
(7)00002.0
00002.000002.0001.0001.0001.0222.0
369.0215.0306.0188.1207.1392.0663.0516.4
43
423241321
2
4
2
3
2
2
2
14321
XX
XXXXXXXXXX
XXXXXXXy
−
−−−+++
+−−++++=
For determination the significance of parameters in the above model, table (4) clearly shows
Y (observed experimentally value) and y (predicated value by model) and its possible to compute the
residual value as
(8)Y-y iii =E
2
iE Value which are tabulated in the last column in table (4), this can be used to calculate 2
iE∑ .
An estimate of the experimental error variance Sr2
which calculated as following:
009057.0
13
117735.0
S
tscoeeficienmodelofnumberin15
experimatstheofnumberis28
131528
2
2
r ==
Σ
=
=−=
γ
γ
iE
The estimated variance of coefficients under nomenclature 2
bS was calculated by the
following formula:
(9)2
2
2
∑
=
X
S
S r
b
Where ∑X2
represents the sum of square of the corresponding elements of variable

53
Table 6: F-test results for the mathematical model coefficients
Coefficient. B B2
∑ X2 Variance
Sb2
=Sr2
/∑ X2
F value
=B2
/Sb2 F0.95(1,13)=4,6
B1 0.663332 0.440009 24 0.000377 1165.974 S*
B2 0.391681 0.153414 24 0.000377 406.5296 S
B3 1.206632 1.455961 24 0.000377 3858.128 S
B4 1.188301 1.41206 24 0.000377 3741.795 S
B5 -0.30639 0.093875 48 0.000189 497.5161 S
B6 -0.21515 0.046287 48 0.000189 245.3129 S
B7 0.369859 0.136796 48 0.000189 724.9844 S
B8 0.22235 0.049439 48 0.000189 262.0172 S
B9 0.001227 1.51E-06 16 0.000566 0.00266 NS**
B10 0.001227 1.51E-06 16 0.000566 0.002659 NS
B11 -0.00127 1.62E-06 16 0.000566 0.002867 NS
B12 -2.4E-05 5.52E-10 16 0.000566 9.76E-07 NS
B13 -2.4E-05 5.52E-10 16 0.000566 9.76E-07 NS
B14 -2.4E-05 5.52E-10 16 0.000566 9.76E-07 NS
• *Significant
• ** non-significant
The F-test application lead to change the equation (3) to below equation (10) after we
canceled the non-significant coefficients
(10)222.0
369.0215.0306.0188.1207.1392.0663.0516.4
2
4
2
3
2
2
2
14321
X
XXXXXXXy
+
+−−++++=
According to equation (10) and by using Hook & Jeeves pattern [9], the optimum conditions
were obtained .The optimum condition of studied variables in coded and real form are listed in
table (7).
Table 7: optimum conditions in coded and real values
Variables Optimum
coded Real
X1 = Formalin concentration (M) -1.08 0.1125 M
X2 = Copper sulfate concentration (M) -0.91 0.0159 M
X3 = Temperature (° C) 1.63 66.3 C
X4 = pH 2.67 13.33

54
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
CopperlayerThikness(µm)
Reduction ion Conc. (M)
Figure (1): shows the effect of reduction ion concentration (formalin) on the deposited copper layer
thickness
9.00
9.50
10.00
10.50
11.00
11.50
0 0.01 0.02 0.03 0.04 0.05
CopperlayerThicness(µm)
Copper ion Conc. (M)
Figure (2): shows the effect of CuSO4 concentration on the deposited copper layer thickness
Dumesic et al. [10] using formaldehyde as a reducing agent he was reported that an increase
in the formaldehyde concentration from 0.03 to leads to a linear increase in the initial deposition, and
this is agree with figure (1).
The overall reaction for electroless copper deposition, with formaldehyde (HCHO) as the
reducing agent, is;
Cu+2
+ 2 HCHO + 4 OH -
= Cu + 2HCOO -
+2H2O+H2 (11)
The effect of copper ions concentration on copper deposited layer thickness is shown in
figure (2); there are high rate in increasing of copper deposited layer thickness through increasing in
CuSO4 concentration, and this come from the fact that CuSO4 represent the copper ions source,
which has ability to deposit under the experimental conditions.

55
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
0 10 20 30 40 50 60 70 80
CopperLayerThicness(µm)
Temperture (° C )
Figure (3): shows the effect of solution temperature on the deposited copper layer thickness
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
10.5 11 11.5 12 12.5 13 13.5
CopperLayerThicness(µm)
pH solution
Figure (4): shows the effect of solution pH on the deposited copper layer thickness
Electroless copper deposition is affected by the pH in two distinct ways. First, OH-
ions are
reactants in the overall reaction (equation 11) and the below partial anodic reaction.
Hydrolysis of Formalin: H2CO + H2O →H2C (OH)2 (12)
H2C (OH) 2 + OH-
→ H2C(OH)O-
+H2O (13)
H2C(OH)O-
→[HC(OH)O-
] ads +H ads (14)
Where the subscript ads denote adsorption of species and [HC(OH) O-
] ads is electroactive
species. Charge transfer, the electrochemical oxidation (desorption)of electroactive species, proceeds
according to the reaction.
[HC(OH)O-
] ads + OH-
→ HCOO-
+H2O + e (15)
Thus influence these reactions in a direct way (primary pH effects).Second, pH affects
various phenomena associated with the structure and composition of the metal–solution interphase.

56
All these phenomena modulate the rate of electroless copper deposition in an indirect way
(secondarypH effects).
CONCLUSIONS
The Box-Wilson statistical experimental design procedure was seen to be applicable in
modeling to evaluate the effect of important variables on copper electroless plating.
The second order polynomial regression analysis of response y (deposited copper layer
thickness) in term of four variables (i.e. concentration of reduction agent formalin (X1), copper ion
concentration (X2), operating temperature (X3), and solution pH (X4) gives equation (10) which
adequately describes the behavior of the electroless copper plating through studied range.
The optimum conditions as predicated is concentration of reduction agent formalin
(0.1125 M), copper ion concentration (0.0159 M), operating temperature (66.3 ӷ C), and solution pH
(13.33).
The deposited copper layer thickness increasing with increased in all four variables, these
increasing continue until they reached to the optimum point and full down.
ACKNOWLEDGMENTS
The author would like to thank the Electrochemical Engineering Department at Babylon
University for supporting and approving this research.
REFERENCES
[1] Klein et al., Electroless Plating Bath Composition and Method of Use, US patent 7686874
B2, Mar. 30, 2010.
[2] Jun Li and Paul A. Kohl. The Acceleration of Nonformaldehyde Electroless Copper Plating,
Journal of the Electrochemical Society, 149 (12) C631-C636 (2002).
[3] Morishata et al. Electroless copper solution, US patent 40999741, Jul. 11, 1987.
[4] T. Anik et al. Influence of pH Solution on Electroless Copper Plating Using Sodium
Hypophosphite as Reducing Agent, Int. J. Electrochem. Sci., 7 (2012) 2009 – 2018.
[5] MichinariSone et.al, Electroless copper plating using FeII as a reducing agent,
ElectrochimicaActa 49 (2004) 233–238.
[6] Zivorad R. Lazic, Design of Experiments in Chemical Engineering, Wiley-VCH
VerlagGmbh& Co. KGaA, Germany, 2004.
[7] Anderson, Chem. Eng. Prog., vol. 55, No. 4, (1959) P. 61, Statistics in the Strategy of
Chemical Experiment.
[8] William &Gertruds, Experimental Design, John Wiley & Sons, Inc., London, (1956).
[9] Jeffwn and Hamada, Experiments; Planning, Analysis, John-Wiley and sons, New York,
2000.
[10] J. Dumesic, The Rate of Electroless Copper Deposition by Formaldehyde Reduction, J.
Electrochem. Soc., 121(1974) 1405.
[11] Hameed Hussein Alwan, “Adsorption Mechanism for Corrosion Inhibition of Carbon Steel
on HCl Solution by Ampicillin Sodium Salt”, International Journal of Advanced Research in
Engineering & Technology (IJARET), Volume 4, Issue 7, 2013, pp. 236 - 246, ISSN Print:
0976-6480, ISSN Online: 0976-6499.

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