Department of Mechanical Engineering, Jadavpur University, Kolkata 700032, India

Abstract

The present study investigates the significance of different coating process parameters on the corrosion behaviour of electrolessly deposited Ni-P-W coatings on mild steel substrate. The process parameters considered are concentration of nickel source, concentration of reducing agent, concentration of tungsten source and annealing temperature. The corrosion characteristic is evaluated by electrochemical impedance spectroscopy technique. The responses considered are charge transfer resistance and double layer capacitance. The Taguchi technique coupled with grey analysis is employed to find out the optimum combination of the process parameters for better corrosion resistance. Analysis of variance (ANOVA) reveals the contribution of the process parameters on the corrosion property of Ni-P-W coating. Finally a validation test is performed to justify the experimental result. The microstructure of the surface is studied by scanning electron microscopy (SEM); energy dispersive x-ray analysis (EDX) reveals the chemical composition and the x-ray diffraction analysis (XRD) is used to identify the phase transformation behaviour of the coating.

Keywords: electrochemical impedance spectroscopy, corrosion, Ni-P-W coating, optimization.

Introduction

Different properties of the external surface of any engineering material, like corrosion resistance, hardness, etc., can be enhanced by coatings for a quite long period of time. The coating protects the substrate materials from the environmental hazards by creating a barrier between the material and the environment. Among all the coating processes, the electroless plating process is considered the most convenient one due to its simplicity and enhanced properties like improved friction, wear and anti-corrosion resistance. According to the classic corrosion theory, nanocrystalline materials should have very poor corrosion resistance because their huge quantity of grain boundaries, acting as the preferential corrosion paths, can accelerate corrosion by forming large number of micro electrochemical cells with the matrix. The basic hypophosphite reduced Ni-P and borohydride reduced Ni-B coatings have proved their supremacy in providing improved hardness, corrosion and wear resistance [1-5].

The corrosion resistance of electroless Ni-P coatings is very much dependent on the phosphorous content of the coating. Electroless Ni-high P coating is effective in offering an excellent protection, whereas electroless Ni-low P and Ni-medium P coatings are not recommended for severe environments [6]. It is obvious that increase in coating porosity decreases the corrosion resistance of the coating. The important factor that affects the coating porosity and ultimates resistance to corrosion attack is surface roughness which is influenced by mechanical preparation of the surface and electroless nickel coating process procedure [7]. Advances in the chemical tailorability of composite coatings have lead to create long-lived, corrosion-resistant, composite coatings. Recently, much attention is being paid towards composite electroless nickel plating. The properties of composite electroless nickel coatings are often superior to those of basic Ni-P and Ni-B [2]. The functional composite coatings with specific characteristics such as wear, corrosion resistances and/or high hardness can be produced easily by choosing suitable particulate materials. The traditional electroless composite coatings have been prepared by adding micro-meter particles to an electroless bath such as SiC, BN, PTFE, diamond [8]. Bigdeli and Allahkaram [6] even found the corrosion resistance of Ni-P-SiC coating better than that of plain Ni-P coating. This effect they ascribed to a reduction in the effective metallic area available for corrosion in Ni-P-nano SiC coating. They also observed that heat- treatment at 400 °C for 1 h significantly improved the coating density and structure, giving rise to an enhanced corrosion resistance for the applied binary electroless nickel and electroless nickel composite coatings. Newly developed Ni-P alloy coatings have been recently reported by the introduction of a third element such as tungsten to form ternary Ni-P-W [9-12]. Published data showed that inclusion of tungsten in binary Ni-P deposit positively affects the deposition rate, composition and deposit properties such as hardness, thermal stability, wear, corrosion resistance and melting point [11]. Compared to electroless Ni-P coatings, incorporation of a third element into Ni-P based coating, for instance, electroless Ni-W-P coatings, significantly influence the thermal stability and crystallization behavior of the coatings by suppression of Ni3P nucleation [12]. Ni-W-P coatings also exhibit higher wear resistance [13]. However, the influence of addition of W on corrosion resistance has been reported by various researchers. Palaniappa and Seshadri [14] reported that improved corrosion resistance (non-deaerated condition) was found with increasing the W content in electroless Ni-P matrix. It was also reported that the corrosion behavior of the electroless Ni-P plating in 0.5 M H2SO4 solution was improved by addition of W, due to the formation of protective films of W oxides [15]. In addition, Gao et al. [16] reported a comparative study for electroless Ni-P and Ni-W-P coatings, when the coatings were heat-treated at 300 °C and 350 °C, respectively, to form a single-Ni nanocrystalline structure, the coatings presented different corrosion performances. The binary Ni-P nanostructure itself was harmful to the corrosion resistance. However, the addition of a third passivation element, W, significantly improved the corrosion resistance of the alloys due to the huge amount of grain boundary diffusion paths provided by the nanostructure, which favored the formation of the dense tungsten oxide film on the surface. It was found that the annealed ternary Ni-W-P alloys had corrosion resistance higher than their amorphous counterpart. Corrosion resistance of an electroless Ni-P-W coating is a function of its chemical composition and post deposition heat treatment. As corrosion is a deteriorating phenomenon so it is needed to optimize the chemical composition to have a better corrosive property.

The studies of the corrosion behaviour of electroless nickel coating are mainly conducted through electrochemical tests viz. potentiodynamic polarization studies and electrochemical impedance spectroscopy. The resistance of the coatings towards corrosion is evaluated on the basis of the corrosion parameters obtained from these studies viz. corrosion potential, corrosion current density, charge transfer resistance, double layer capacitance, corrosion rate, etc. [17-19]. The electrochemical impedance spectroscopy (EIS) technique has proven to be a valuable test method for the electrochemical characterization of the protective coating on metals. This method provides very detailed data on the effectiveness of a coating over a relatively small area. The EIS technique can indicate the presence and rate of corrosion, and the moisture content of the coating prior to corrosion [20]. Thus, the EIS technique is chosen to characterize the corrosion behavior of the coatings in the present study. Taguchi method together with Grey relational analysis is employed to optimize the process parameters in order to identify the combination of parameters that induce the maximum corrosion resistant properties in the coating. Analysis of variance is employed to observe the contribution of the main design factors and their interactions. Finally, validation of the result obtained through the analysis is done with the help of confirmation test. The microstructure, chemical composition and phase transformation behaviour of Ni-P-W coatings are studied with the help of scanning electron microscopy, energy dispersed X-ray analysis and X-ray diffraction analysis, respectively.

Taguchi design methodology

Most of the engineering problems deal with the optimization of the design parameters to achieve the desired performance characteristics. The Taguchi technique is the most convenient method used by engineers to optimize any engineering problem. The Taguchi design technique consists of three consecutive stages such as system design, parameter design, and tolerance design. System design is the usage of scientific and engineering information required for producing a part. Parameter design is used to obtain the optimum levels of process parameters for developing the quality characteristics and to determine the product parameter values depending on the optimum process parameter values. Tolerance design is the stage to determine and to analyze tolerances about the optimum combinations suggested by parameter design. The aim of this study is to optimize the corrosion behaviour of chemically deposited Ni-P-W coating using grey based Taguchi method [21]. The concept of the Taguchi method is to optimize process parameters to achieve high quality with low cost. This technique is widely used in the engineering domain to get the desired performance characteristics by optimizing the design parameters. Taguchi recommends the use of the loss function to measure the quality characteristic. The value of the loss function is further transformed into a statistical measure called signal-to-noise (S/N) ratio. S/N ratio, being the ratio of mean to standard deviation, can effectively consider the variation encountered in a set of trials. A larger S/N ratio represents minimization of noise factor, thus a better quality characteristic and the corresponding process parameters are incentive to the variation of environmental conditions and other noise factors. Due to the increasing number of process parameters, a special design of orthogonal arrays (OA) is used in the Taguchi method to reduce large number of experiments that need to be carried out. Based on the objective of the experiment, S/N ratio characteristics can be divided on the basis of three criteria: lower-the-better (LB), higher-the better (HB) and nominal-the best (NB).

Grey relational analysis

The present study aims to evaluate the electrochemical characteristics of electroless Ni-P-W coating with the help of electrochemical impedance spectroscopy (EIS) considering two main response parameters viz. charge transfer resistance and double layer capacitance. The objective is to maximize the corrosion resistance. Thus it becomes a multi-response objective function optimization, which differs from the single response optimization. Grey relational analysis is one of the efficient tools, which can be employed for the overall evaluation of the S/N ratio to optimize the multiple response characteristics. Any system in nature is neither full of precise information (white) nor completely lack of information (black); mostly they consist of partial information (mixture of white and black called grey). The main objective of the grey theory is to supply sufficient information so that one can whiten the greyness. Grey relational analysis is based on the grey system theory and compares and computes the dynamic casualities of the subsystems of a given system. The first step in performing the grey relational generation is to normalized results of the experiments in the range between 0 and 1. Then the second step is to calculate the grey relational coefficient from the normalized data to represent the correlation between the desired and actual experimental data. Finally, the overall grey relational grade is computed by averaging the grey relational coefficient corresponding to each performance characteristics. Considering this grey relational grade the overall evaluation of the multiple response characteristics is done. A statistical analysis of variance (ANOVA) is performed to find the statistically significant parameters of the experiment. With the grey relational analysis and statistical analysis of variance, the optimal combination of the process parameters can be predicted. Finally, a confirmation experiment is conducted to verify the optimal process parameters obtained from the analysis.

Materials and coating method

The Ni-P-W coating is deposited on mild steel (AISI 1040) specimen of size 20 mm × 20 mm × 8 mm. Shaping, parting, milling processes are used accordingly for the preparation of the sample. The sample is then subjected to surface grinding process. The sample is mechanically cleaned from foreign matters and corrosion products. After that the MS sample is cleaned using distilled water followed by a pickling treatment with dilute (50%) hydrochloric acid for one minute to remove any surface layer formed like rust. Then the sample is rinsed in distilled water and methanol cleaning. A large number of trial experiments are performed before deciding the bath composition.

Nickel sulphate is used as the source of nickel, while sodium hypophosphite is the reducing agent which reduces the nickel into its elemental form while itself getting oxidized. Sodium tungstate solution is used as the source of tungsten ion. The bath is prepared by adding the constituents in appropriate sequence. The pH of the solution is maintained around 7-8 by continuous monitoring with a pH meter. The steps for obtaining the Ni-P-W deposit are as follows:

• the samples are cleaned using acetone followed by a pickling treatment using 50% dilute hydrochloric acid;

• the substrates are then activated in palladium chloride solution at a temperature of 55 °C;

• activated samples are then submerged into the chemical bath which is maintained at a temperature between 90-92 °C with the help of a hot plate cum stirrer, attached with a temperature sensor which is also submerged in the solution;

• the range of coating thickness is found to lie around 25-30 microns;

• after deposition, the samples are taken out of the bath and cleaned using distilled water;

• after the coating the samples are heat treated at different temperatures (400 °C, 500 °C and 600 °C) according to the design of experiment.

Selection of design parameters

Three levels, having equal spacing, within the operating range of the parameters were selected for each of the factors. By selecting the three levels, the curvature or non-linearity effects could be studied.

Response variables

Design of experiments

Each row in the table represents a specific combination of experimental run and each column represents a specific factor or interactions. The cell value indicates the level of the corresponding factor or interaction assigned to that column. However, the experimental run is controlled by the settings of the controllable design factors, i.e., A, B, C and D, and not by the interactions.

Characterization and surface morphology

Energy dispersive X-ray (EDX) analysis is done in conjunction with SEM to study the composition of the EN coatings in terms of the weight percentages of nickel, phosphorous and tungsten in the coatings before and after heat treatment at different temperatures. EDX is done in an EDX analyzer (EDAX Corporation). The surface morphology of the coating is observed through scanning electron microscope (SEM) (JEOL, JSM 6360) in order to analyze the effect of heat treatment on the microstructure of the deposits. The phase structures were studied by the X-ray diffractometer (Rigaku, Ultima III) both before and after heat treatment.

Electrochemical impedance spectroscopy (EIS) test

The charge transfer resistance (R_ct) is represented by the resistance of electron transfer during electrochemical reaction course. The double layer capacitance (C_dl) can be correlated to the delamination of the coating. Solution resistance (Rs) is referred to the resistance between the work electrode and reference electrode. The values of charge transfer resistance (R_ct) and double layer capacitance (C_dl) were determined from the Nyquist plot by fitting a semicircle using the accompanying software.

Results and discussion

Characterization and morphology of the coating

It is clear that the deposit has globular like shape without any porosity in as deposited condition. When it is heat treated at 500 °C the globules become more compact and produce a dense structure resulting harder deposit. With further heating at 600 °C the size of the globule increases and transforms into coarse grained structure.

Grey analysis

Step 1: Normalization of responses

The first step for generating the grey relational coefficient involves the linear normalization of the experimental results (R_ct and C_dl) in the range between 0 and 1. A material will have lower tendency to corrode if the R_ct value tends to higher with a lower value of C_dl. So higher the better criterion for R_ct and lower the better criterion for C_dl are used for normalization.

Expression for higher the better:

Expression for lower the better:

Step 2: Generation of grey relational coefficient

From the normalized value the grey relational coefficient is calculated by applying the equation

Analysis of signal to noise (S/N) ratio

Taguchi method uses S/N ratio to convert the experimental results into a value for the evaluation characteristic in the optimum parameter analysis. Where signal means desirable value (mean) and the noise is the undesirable value (S.D.). A larger S/N ratio represents a better quality characteristic because of the minimization of noise and the corresponding process parameters are incentive to the variation of environmental conditions and other noise factors. The variability can be easily captured if S/N ratio is used to convert the experimental results into a value for the evaluation characteristic in the optimum parameter analysis, instead of the mean. The idea is to maximize the S/N ratio, thereby minimizing the effect of random noise factors, which have a significant impact on the process performance. As the grey relational grade has to be maximized so higher the better criterion is used to calculate the S/N ratio, expressed as:

All the calculations are performed using Minitab [25].

The response table shows the average of the selected characteristic for each level of the factors. The response table includes ranks based on Delta statistics, which compare the relative magnitude of effects. The Delta statistic is the highest average for each factor minus the lowest average for the same. Ranks are assigned based on Delta values; rank 1 is assigned to the highest Delta value, rank 2 to the second highest Delta value, and so on.

In the main effects plot if the line for particular parameter is near horizontal, then the parameter has no significant effect. On the other hand, a parameter for which the line has the highest inclination will have the most significant effect. It is very much clear from the main effects plot that parameter C (concentration of tungsten source solution) is the most significant parameter, while parameter D (annealing temperature) also has some significant effect.

The ANOVA table shows the percentage contribution of each parameter. It is seen that parameter C, i.e., concentration of tungsten source solution and parameter D, i.e., annealing temperature, have the major contribution on electrochemical behaviour of Ni-P-W coating within the specific test range. Among the interactions, the interaction of parameters between B and C has significant contribution. This type of analysis is not available in the literature and will be useful for Ni-P-W coating deposition with an objective of optimum corrosion behaviour within the particular range of process parameters.

Validation test

After obtaining the optimal level of coating process parameters, the final step is to predict and verify the improvement of the performance characteristic using the optimal level of the process parameters. The estimated grey relational grade, η̂, using the optimal level of the process parameters can be calculated as:

It can be seen that both the plots exhibit a semicircular nature in the higher frequency region but the semicircles have different sizes. This indicates that the same corrosion phenomenon is occurring but over a larger area. Also their corrosion properties are different and enhanced with the annealing temperature above 500 °C for the optimum combination of coating parameters obtained from this analysis.

Conclusion

Ni-P-W alloy films are deposited on mild steel substrate from the electroless bath and the corrosion behaviour (electrochemical impedance spectroscopy) in 3.5% sodium chloride solution are studied. Here the Taguchi orthogonal array coupled with grey relational analysis is employed to optimize the coating process parameters for maximum corrosion resistance. The optimum parameter combination is found to be A3B2C3D3, i.e., nickel concentration 30 g/L, reducing agent concentration 17 g/L, tungsten concentration 25 g/L and annealing temperature 600 °C. ANOVA result indicates that concentration of tungsten source (C) is the most important parameter that significantly affects the corrosion characteristics. Also, the interaction between the reducing agent and the tungsten source is significant. The improvement of the grey relational grade from the initial condition to the optimal condition is found to about 56%. From the EDX analysis it is clear that the coating is pure ternary and consists of nickel, phosphorous and tungsten. The XRD plots reveal that the coating is a mixture of amorphous and crystalline structure in the as deposited condition and produces Ni-W and Ni3P as major compounds after heat treatment at 500 °C for 1 hour. From the surface morphology captured by SEM it is seen that there are many globular particles on the surface of the substrate with no surface damage.

References