Arab J Sci Eng (2016) 41:591–598 DOI 10.1007/s13369-015-1700-3
RESEARCH ARTICLE - MECHANICAL ENGINEERING
Effect of Electrophoretic Deposition Parameters on the Corrosion Behavior of Hydroxyapatite-Coated Cobalt–Chromium Using Response Surface Methodology Mostafa Rezazadeh Shirdar1 · Sudin Izman1 · Mohammad Mahdi Taheri2 · Mahtab Assadian2 · Mohammed Rafiq Abdul Kadir3
Received: 20 October 2014 / Accepted: 17 May 2015 / Published online: 29 May 2015 © King Fahd University of Petroleum & Minerals 2015
Abstract Cobalt–chromium (Co–Cr)-based alloys have been used extensively as medical implants, but the ion release and the corrosion products can affect their mechanical integrity and biocompatibility. One of the solutions is to surface coat the substrate with hydroxyapatite via electrophoretic deposition technique. Two variables—pH of electrolyte and current density—were used to examine the electrochemical behavior of the coated sample. An experimental strategy was developed based on the response surface methodology together with the analysis of variance to verify the precision of the mathematical models and their relative parameters. Close agreement was observed between the predicted models and the experimental results. The pH value of electrolyte was a more significant factor than current density in increasing the corrosion potential (E corr ) of the substrate.
B
Mohammed Rafiq Abdul Kadir
[email protected] Mostafa Rezazadeh Shirdar
[email protected] Sudin Izman
[email protected] Mohammad Mahdi Taheri
[email protected] Mahtab Assadian
[email protected]
1
Department of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
2
Department of Materials Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
3
Medical Implant Technology Group (MEDITEG), Faculty of Bioscience and Medical Engineering, Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor Bahru, Johor, Malaysia
The maximum E corr was obtained with a current density of 12 mA cm−2 and a pH value of 4.71. Keywords Cobalt–chromium · Electrophoretic deposition · Hydroxyapatite · Response surface methodology · Electrochemical corrosion behavior
1 Introduction Cobalt–chromium alloys have been widely used as orthopedic implants due to their wear resistance in vivo and superior stiffness compared with titanium alloys and stainless steels [1]. However, their use in hostile electrolytic environments such as in human body fluid is limited due to ion release [2], slow osseointegration and lack of bioactivity [3]. The ion release and corrosion products can adversely affect the mechanical integrity and biocompatibility [4,5] and also lead to infection, swelling, loosening and local pain [6]. Coating their surfaces with hydroxyapatite (HA), which is the main inorganic component of human bones and teeth, has been widely used to enhance their biocompatibility while maintaining their mechanical strength [7,8]. The thin film of HA on the metallic implant such as Co–Cr can increase its corrosion resistance and also enhance the biological interaction between implant surface and surrounded tissues [9]. There have been many reports of HA coating methods on various metallic substrates, such as plasma spraying [10], biomimetic coating [11–13], investment casting [14], sol–gel [15,16] and electrophoretic deposition (EPD) [17,18]. Compared with other techniques, EPD requires a relatively simple setup [19] and does not require the use of a high temperature [20]. In the EPD process, charged particles deposited onto an electrode under the influence of an applied electric field. The characteristics of this process are determined by
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two groups of parameters: (1) those related to the process such as current density and deposition time and (2) those related to the suspension such as pH of the electrolyte. The thickness of coatings and their morphology vary depending on the EPD parameters such as the current density and pH of the electrolyte [19]. It has been reported that the coating morphology affects the corrosion resistance of HA scaffold [21] and HA-coated metallic substrate [22]. The EPD technique has been used before to coat HA on other biometallic materials such as stainless steel [18] and titanium [23,24], where different EPD parameters were reported for optimum coating performance. However, the technique has so far not been used to coat Co–Cr alloys. In order to increase demand for the use of Co–Cr alloys, we analyzed two EPD parameters to attain the best coating performance in terms of corrosion potential. Although other analysis and prediction methods such as fuzzy logic [25] and Taguchi [26] methods have been utilized in different process, in this study an experimental strategy based on the response surface methodology (RSM) was used with analysis of variance (ANOVA) to investigate the effect of current density and pH of the electrolyte on the corrosion potential of the HAcoated Co–Cr alloy. Finally, a precision mathematical model was created based on the effective parameters and their interactions which can be used for the prediction of the corrosion potential of the coated substrate. The predicted model generated by RSM was then compared with the experimental results to evaluate its accuracy.
2 Materials and Methods 2.1 Materials A cylindrical bar of wrought Co–28Cr–6Mo alloy with a diameter of 10 mm was cut into disks of 2 mm thickness using a precision cutting machine. Samples were polished with abrasive silicon carbide papers (320–1200 grit) and then ultrasonically cleaned with acetone for 10 min. 2.2 HA Coating and Electrochemical Test Electrolyte was prepared by mixing Ca(NO3 )2 · 4H2 O and NH4 H2 PO4 [18], with the Ca/P ratio being 1.67 in DI water with pH values of 3, 4 and 5 adjusted by adding HNO3 and (CH2 OH)3 CNH2 [27]. The electrolyte was rendered homogeneous by continuous stirring at 100 rpm for 24 h. The EPD process was performed by a regulated DC power supply (DYY-6C, BEIJING LIUYI) in a current density of 6, 9 and 12 (mA cm−2 ). The criteria for selection of current density and pH were based on the minimum value that deposition occurs and maximum ones which would not lead to creation of crack and peeling of the coated layer. The substrate,
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Table 1 Factors and their levels Factor
Symbol
Levels −1
0
+1
Current density (mA cm−2 )
A
6
9
12
pH
B
3
4
5
Co–Cr alloy, acted as the cathode, while a graphite electrode was used as the anode. Deposition was carried out in 20 min at room temperature (25 ◦ C). After coating with calcium phosphate, the specimens were removed from the electrolyte solution, rinsed in distilled water and dried at 60 ◦ C for 24 h. Then, the as-deposited sample was sintered at 800 ◦ C for 1 h in a vacuum furnace at 10−5 torr [28]. Potentiodynamic polarization studies of the non-coated and HA-coated samples were carried out using a potentiostat corrosion test machine (Princeton Applied Research, AMETEK, versaSTAT 3). A three-electrode cell was used for electrochemical measurements, including a reference electrode [saturated calomel electrode (SCE)], counter electrode (graphite rod) and working electrode (the specimens) [29]. The tests were carried out in 500 mL of simulated body fluid (Kokubo solution [(mmol/L) 142 Na+ , 5 K+ , 2.5 Ca2+ , 1.5 Mg2+ , 4.2HCO3− , 147.8 Cl− , 1 HPO4 2− , 0.5 SO4 2− ]) with a pH of 7.6 and a temperature of 37 ◦ C [27]. 2.3 Design of Experiments In order to study the effect of electrophoretic parameters on the electrochemical corrosion behavior of HA-coated Co–Cr alloy, two independent factors—pH of electrolyte and current density—were analyzed as shown in Table 1. The Design Expert software (Stat-Ease, USA) was used for the statistical design of the experiments and data analysis. The corrosion potential (E corr ) of the coated specimens was investigated using the standard RSM design known as the central composite design (CCD). The factorial portion is a full factorial design, with all of the combinations of the factors at three levels, and the star points are located on the faces of the cube in the design, with two replicates. The star points correspond to an α value of 1, and this design is commonly referred to as a face-centered CCD. The center points are points with all levels set to coded level 0; the midpoint of each factor range is repeated three times. Eighteen performance tests were performed. Table 1 shows the experimental plan for two factors and three levels. 2.4 Response Surface Methodology In an engineering process, when the response is influenced by several variables, a useful statistical and mathematical method such as response surface methodology (RSM)
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is useful for analysis and modeling of the problem. Due to the unknown relationship between independent variables and response, the first step in RSM is to discover a proper approximation for the true functional relationship between the response “y” and a set of independent variables {x1 , x2 , . . . , xn } [30]. A quadratic model is applied when the response function is nonlinear or unknown [31]: Y = β0 +
k
βi X i +
i=1
k
βii X i2
i=1
+ ··· + e
k k i i≤1
βi j · X i · X j
j
(1)
where i determines the linear coefficients, j specifies the quadratic coefficients, b represents the regression coefficients, k is the number of experimental factors and e is the random error. Analysis of variance (ANOVA) is employed to estimate the stability of generated regression model. The term F ratio, the ratio of the variance due to the effect of each model factor and the variance resulting from the error terms, is calculated using ANOVA procedure. The significance of the model using the variance of all of the terms at an appropriate level, α, is determined by F value. The P value known as the probability of significance is determined in the first step. The effect of the independent variable is significant if the P value is equal to or less than the selected α-level, and the insignificant variables are those with P values greater than the selected α-level [32]. Degree of freedom (DOF) is the number of values in the final calculation of a statistic that are free to vary. The null hypothesis tested in the ANOVA table is that all of predictor variable coefficients are equal to zero. The null hypothesis is that there are no coefficients to be estimated. The alternative hypothesis is that there are P coefficients to be estimated. Therefore, there are P-0 or P degrees of freedom for testing the null hypothesis. This accounts for the regression DOF in the ANOVA table. 2.5 Characterization In order to investigate the evaluation of surface morphology and composition, series of characterizations have been carried out. The crystallography and phase transformation were evaluated using an X-ray diffractometer (Siemens-D5000). The compositions of the coating layers were obtained from Fourier transform infrared (ATR-FTIR, Nicolet iS5, thermo scientific, USA). Microstructural observations were performed using a scanning electron microscope (SEM, JEOL JSM-6380LA), equipped with an EDX.
3 Results and Discussion The potentiodynamic polarization tests were undertaken in a simulated body fluid (SBF) solution. The corrosion
Table 2 Experimental results Sample no. 1
Run
5
Current density (mA cm−2 ) 6.00
pH
Corrosion potential (mV)
3.00
337
2
6
6.00
3.00
358
3
3
12.00
3.00
385
4
11
12.00
3.00
417
5
10
6.00
5.00
699
6
8
6.00
5.00
643
7
15
12.00
5.00
851
8
7
12.00
5.00
814
9
12
6.00
4.00
679
10
13
12.00
4.00
773
11
1
9.00
3.00
337
12
16
9.00
5.00
698
13
17
9.00
4.00
659
14
18
9.00
4.00
631
15
4
9.00
4.00
611
16
2
9.00
4.00
669
17
9
9.00
4.00
701
18
14
9.00
4.00
661
potential of the HA-coated samples prepared in all conditions of deposition in terms of pH and current density is shown in Table 2. These results were used as input into the Design Expert software for further analysis. The model summary statistics for corrosion potential are given in Table 3. The fit summary output reveals that the best models are quadratic models. Thus, quadratic models are used for further analysis.
3.1 Analysis of Variance (ANOVA) ANOVA was applied to test for the significance of the regression model, the test for significance on individual model coefficients and test for lack of fit. The ANOVA table for the response surface quadratic model for corrosion potential is presented in Table 4. Values less than 0.050 for “Prob > F” indicate that the model is significant, which is desirable as it reveals that the terms in the model have a significant effect on the response. The results showed that factors A, B, AB, A2 and B 2 are all significant, with factor A (current density) the most significant. The “lack of fit F value” of 0.26 implies that the lack of fit is not significant relative to the pure error, and it is desirable. There is a 0.8549 % probability that a “lack of fit F value” with such a large value could occur due to noise. Equations 1 and 2 are the final empirical models for corrosion potential in terms of coded and actual factors, respectively:
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Table 3 Model summary statistics for corrosion potential
Table 4 ANOVA for the response surface quadratic model
Source
Adj. R 2
R2
SD
Pred. R 2
PRESS
Linear
76.47
0.8115
0.7863
0.7261
1.274E+005
Interaction
76.48
0.8240
0.7863
0.7171
1.316E+005
Quadratic
26.67
0.9817
0.9740
0.9614
17,961.54
Suggested
Cubic
28.90
0.9821
0.9695
0.9388
28,455.57
Aliased
Source
Sum of squares
Model
4.567E+005
A–I
27,457.60
B–pH
Mean square
F value
P value Prob > F
5
91,342.00
128.46
