This paper investigates the assessment of the mixing effect of zinc-silica composite electrolyte using particle image velocimetry (PIV). In particular, we considered the deposition of silica particles using a stirring tank, which provides strong evidence for characterizing the mixing effects of flow field. A method to extract meaningful parameters to evaluate particle distribution from digital images recorded by the PIV technique during the electrodeposition process is applied. The Betti numbers of binary images of silica particles mixing were calculated using the CHomP software, which was used to evaluate mixing homogeneity and nonhomogeneity in flow field. An analysis of the performance of zinc-silica composite coatings is performed in an attempt to test and verify the assessment of the effects of micron-particle aggregation. Good correlations between calculated and experimental testing results illustrate the potential of the Betti numbers method to quantitatively evaluate micron-particle aggregation. This offers new possibilities to monitor the deposition of silica particles and to analyze flow field during the electrodeposition progress.
Composite electrodeposition, an important technology for metal surface treatments, is widely used to make metal-matrix composites and multifunctional composite cladding materials [
In the case of composite electrodeposition, stirring in flow field is the key factor affecting the mass transfer, adsorption, and deposition of the solid particles. To understand the basic theory of composite electrodeposition and thus optimize the parameters of the technique, it is essential to understand the flow characteristics of the electrolyte. Zielinski [
The flow state of the electrolyte and the electrochemical reaction on the surface of the negative electrode are two basic scientific questions concerning the composite electrodeposition technique. Currently, there have been numerous reports investigating the electrochemical reaction mechanism along with respective models of composite electrodeposition [
This study mainly focuses on the mixing effect of electrodeposition flow field. By adopting the evaluation method of Betti numbers; the mixing effect can be effectively quantified under different stirring conditions. Finally, by analyzing the capabilities of the resulting cladding material, the effectiveness of the evaluation method and the models of the multiphase mixing effect are verified.
The electrodeposition experiment was performed in a flat rectangular plexiglass tank, of dimensions 150 mm length, 100 mm width, and 120 mm height. The tank was filled with electrolyte up to a height of 100 mm when the stirring paddle remain stationary.. A vertical plate was used for the electroplating with a temperature of 25°C. The composition of the electrolyte was
A viscometer was used to measure the viscosity of the electrolyte. The weighing method was adopted to determine the density of the electrolyte. A laser particle size analyzer was used to determine the distribution of the SiO2 particle size and the dispersion characteristics in the suspending fluid. Solution conductivity was measured using a conductivity meter. Surface tension was determined using a surface tension tester. The testing results are shown in Table
Determination of experimental parameters.
Density of electrolyte | Density of |
Conductivity | Surface tension | Dynamic viscosity | Kinetic viscosity | Average particle size of |
---|---|---|---|---|---|---|
1.16~1.18 g/cm3 | 2.65 g/cm3 | 0.75~0.95 × 103 |
40.5~41.0 mN/m | 1.50~1.52 × 10−3 Pa·s | 1.51~1.53 × 10−6 m2/s | 11.07 |
The stirring rate of the electric stirrer was kept in the range of 0–3000 r/min. The electric current of the electrodeposition device was 0–0.5 A. The size of the stirring paddle was
Experimental setup of electrodeposition ((
From algebraic topology, Betti numbers are defined as follows:
Digital image processing technology was used to process the real-time images of mixing particles in flow field into binary images. The extracted Betti numbers are adopted to quantify the mixing effect in flow field.
In Figure
Mixing image and binary image in electrodeposition.
The effect of electrical field on the micron-particle aggregation is now taken into consideration. The stirring paddle’s height is kept at 10 mm. With the same initial conditions, the particle image velocity (PIV) is calculated at
Velocity distribution at
Velocity distribution at
Thus, in this experiment the effect of electrical field is neglected. The electric current is kept at 0.25 A. Different average rotating speeds of 500 r/min, 1000 r/min, 1500 r/min, 2000 r/min, 2500 r/min, and 3000 r/min were used to conduct the experiments. The vertical distance from the paddle to the bottom of the tank was set in a range between 0 and 30 mm.
First, data from different mixing conditions were collected. A high-speed camera stored the real-time flow field images with a stirring time of 200 s. Second, digital image processing technology was used to process each real-time image of mixing particles in flow field into a binary image. Finally, using the CHomP program, Betti numbers were calculated from the binary images. Curves of 0-dimensional and 1-dimensional Betti numbers as a function of time
Data of minimum mixing time, average 0-dimensional and 1-dimensional Betti numbers, and amplitude at different rotating speeds and paddle heights with
mm | r/min | |||||
---|---|---|---|---|---|---|
500 | 1000 | 1500 | 2000 | 2500 | 3000 | |
10 | ||||||
|
1121 | 1398 | 1364 | 1402 | 1327 | 1362 |
|
156 | 212 | 245 | 238 | 219 | 189 |
|
75 | 21 | 20 | 24 | 18 | 16 |
|
20 | 23 | 21 | 22 | 16 | 17 |
|
||||||
20 | ||||||
|
1167 | 1339 | 1400 | 1322 | 1301 | 1345 |
|
184 | 176 | 268 | 251 | 204 | 198 |
|
68 | 25 | 27 | 19 | 22 | 18 |
|
23 | 25 | 26 | 25 | 17 | 16 |
|
||||||
30 | ||||||
|
1110 | 1295 | 1308 | 1347 | 1289 | 1289 |
|
235 | 221 | 226 | 188 | 171 | 171 |
|
65 | 28 | 19 | 20 | 31 | 31 |
|
27 | 23 | 22 | 19 | 16 | 16 |
Based on a previous study [
The optimal mixing-effect conditions, calculated from the evaluation model, were
Figure
Evolution curves of 0-dimensional Betti numbers.
Figure
Evolution curves of 1-dimensional Betti numbers.
First, an electron probe was used to determine the SiO2 content distribution. The results are compared in Figure
Content distribution of SiO2 in composite coatings using an electron probe.
Secondly, acid was used to dissolve the coating metal to weigh the rest of the mass of SiO2. The amount of SiO2 in different areas of the composite coating was determined by dividing the SiO2 mass by the total weight of the coating before dissolution. Then, a magnetic thickness tester was used to measure the thickness at different areas of 9 well-distributed coatings. Finally, the samples were wax-sealed after drying and tested for ageing by exposing an area of size
SiO2 content (mass %), thickness, and erosion resistance of composite coatings in different areas of iron plate for
Sample no. | SiO2 content [%] | Thickness [ |
Red rust time in NSS [h] |
---|---|---|---|
1 | 0.49/0.47 | 21.5/22.5 | 432/448 |
2 | 0.51/0.49 | 20.6/21.2 | 416/432 |
3 | 0.50/0.49 | 22.5/22.0 | 448/432 |
4 | 0.52/0.50 | 21.2/21.8 | 416/432 |
5 | 0.53/0.51 | 20.5/20.8 | 416/416 |
6 | 0.52/0.52 | 22.0/21.4 | 432/416 |
7 | 0.54/0.53 | 21.5/22.4 | 432/448 |
8 | 0.56/0.55 | 21.2/22.1 | 416/432 |
9 | 0.56/0.54 | 22.4/22.2 | 448/448 |
Table
SiO2 content (mass %), thickness, and erosion resistance of composite coatings in different areas of iron plate for
Sample no. | SiO2 content [%] | Thickness [ |
Red rust time in NSS [h] |
---|---|---|---|
1 | 0.39/0.38 | 18.3/18.4 | 390/406 |
2 | 0.43/0.41 | 22.3/22.1 | 409/425 |
3 | 0.39/0.38 | 19.7/20.1 | 396/412 |
4 | 0.62/0.60 | 21.2/21.8 | 412/428 |
5 | 0.53/0.51 | 20.4/20.7 | 416/432 |
6 | 0.36/0.38 | 18.8/19.2 | 400/416 |
7 | 0.51/0.50 | 22.5/22.3 | 402/402 |
8 | 0.64/0.62 | 20.6/21.1 | 448/448 |
9 | 0.41/0.39 | 18.2/18.5 | 389/405 |
SiO2 content (mass %), thickness, and erosion resistance of composite coatings in different areas of iron plate for
Sample no. | SiO2 content [%] | Thickness [ |
Red rust time in NSS [h] |
---|---|---|---|
1 | 0.64/0.61 | 23.3/23.5 | 401/417 |
2 | 0.50/0.52 | 21.4/21.2 | 410/408 |
3 | 0.34/0.37 | 18.6/18.7 | 386/392 |
4 | 0.62/0.60 | 22.3/22.5 | 432/416 |
5 | 0.55/0.53 | 21.5/21.8 | 432/432 |
6 | 0.37/0.39 | 18.9/20.1 | 388/398 |
7 | 0.45/0.43 | 20.5/20.3 | 393/409 |
8 | 0.51/0.50 | 21.3/21.1 | 409/425 |
9 | 0.61/0.59 | 23.8/23.6 | 432/416 |
In summary, using an electron probe and performance analysis of the coatings, we can conclude that, when the micron-particle aggregation around the negative electrode benefits from an optimal mixing effect, the SiO2 particles are well-distributed and the red rust time in the salt spray test is maintained at over 410 hours; after comparing the capability tests, under other relatively good mixing conditions, their testing points’ capabilities show a large variation, and the overall performance is not as good as the optimal condition where
A composite Zn-SiO2 electrodeposition system and the most widely used stirring method are adopted to explore the flowing characteristics of the electrolyte. In particular, digital image processing technology is used to analyze images of the micron particles’ distribution and aggregation. Meanwhile, the Betti numbers method is used to quantify the mixing effects of the composite electrolyte. The 0-dimensional Betti numbers (
A comparison of the coatings’ performance with relatively good mixing effects is conducted with the assistance of electron probe testing, a thickness tester, and an erosion test. Results show that, under other conditions, there is a big disparity between the 9 testing points and this shows that the overall performance of these conditions are inferior to the optimal condition. This paper verifies the feasibility of the Betti numbers method and model. It will further improve studies of composite electrodeposition fluid mechanics, which provides an important reference to understand the basic scientific questions of electrodeposition and its process optimization.
This work is supported by the Joint Funds of National Natural Science Foundation of China (Grant no. U0937604), the National Natural Science Foundation of china (Grant no. 51361018), and the Nature Science Foundation of Yunnan Province (nos. 2013FB020 and KKSY201258156). The authors wish to especially thank the referees for detailed questions and comments that greatly improved the presentation.