Optimization of the Effects of Electrodeposition Parameters on the Nickel-Based Composite Coatings’ Tribological Properties
Abstract
1. Introduction
2. Metal Matrix Composites
2.1. Methods for Creating Composites Using Metal Matrix
2.2. Electrodeposition of Nanoparticles in a Nickel-Based Matrix
2.3. Tribology Properties
2.3.1. Micro-Hardness and Nano-Hardness
2.3.2. Wear Resistance
- Oxidation (corrosion) of friction surfaces can accelerate wear. High temperatures and the friction-induced loss of protective oxide layers from the surface speed up this process. Friction continuously removes the oxide deposit, preventing new oxide from forming. Hard oxide particles trapped by sliding/rolling surfaces after removal also enhance three-body abrasive wear.
2.3.3. Friction
3. Parameters Affecting the Tribology Property
3.1. Particle-Related Parameters
3.1.1. Type of Nanoparticle
3.1.2. Particle Size
3.1.3. Nanoparticle Concentration in the Bath
3.1.4. Combination of Particles
3.2. Parameters Related to Deposition Energy
3.2.1. Effect of Average Current Density
- Direct Current (DC): Figure 10a illustrates the correlation between the coatings’ current density and the micro- and nanoscale SiC concentrations. At lower current densities, the rate of Ni (II) reduction is slower, giving inert particles ample time to adhere to the electrode surface and become part of the Ni matrix. As current density increases, the SiC content of the coatings decreases because fewer particles may be absorbed into the Ni matrix due to inert particle adsorption, which happens far more slowly than the Ni (II) reduction rate [82]. R.K. Saha et al. demonstrated the same outcome [43]. In the coatings, the mass fraction of Al2O3 particles first increased with current density before peaking at 4.3 weight percent at 0.01 A/cm2. The concentration of particles that were co-deposited did not vary as the current density increased. With a maximum current efficiency of 0.01 A/cm2, more reinforced particles were created by the electrodeposition process. Ni–ZnO composites were discovered to have a nodular shape. Low current densities resulted in compact and smooth Ni–ZnO coatings. As the current density increased, the coatings’ surface became more imperfect and punctured [61]. Using a vertical magnetic field and jet electrodeposition technique, R. An-hua et al. [25] created a Ni-CeO2 nanocomposite coating on a 45# steel substrate. Even though the coatings contained 10–33% mass percentages of MoS2 particles, the composite coating demonstrated a maximum microhardness value of 665.78 HV0.1 at a current density of 20 A/dm2. The hardness, however, dropped from around 650 to 435 after the formation of Ni-MoS2 nanostructures when the current density was raised from 3 to 7 A/dm2. Throughout the treatment, current densities of 10, 15, 20, 25, and 30 A/dm2 were employed, and each component had to be plated for 25 min. The ideal current density for the codeposition of nickel-MoS2 nanostructured composite coatings with a lovely look and advantageous tribological performances was therefore determined to be 5 A/dm2 [59]. Moreover, Figure 10b–f displays the composite coating’s surface look as seen under an electron microscope following 20 min of ball mill polishing. According to the findings, wear scars on the composite coating surface first shrank in width, depth, and cross-sectional area before growing as the current density rose. At low current densities, it was thinner, and the composite covering’s hardness value was lower. Significant adhesive wear caused the covering to deteriorate; mild oxidative and abrasive wear coincided with the rise in current density. When the composite coating’s current density was raised by 20 A/dm2, coating surface attrition decreased. [25].
- Pulsed current (PS): In pulsed current electrodeposition, a cathodic current is applied for a predetermined time (Ton) and then interrupted for a predetermined time (Toff). Higher average current densities (ia) can be used for the electrodeposition procedure since the pulsing of the current inhibits dendritic development [27]. Due to their uniform particle distribution and higher alumina content, Ni–Al2O3 composite coatings produced by pulsed current exhibit better wear characteristics than those deposited by direct current. The higher density of (002) planes is what gives nickel-based coatings their enhanced ductility and growth in the [83] direction, as well as boosting their capacity to absorb plastic deformation energy and inhibiting the development of microcracks. Additionally, the nickel matrix’s greater grain size is thought to be advantageous. Better wear characteristics result from higher Al2O3 concentration combined with high. However, for nanocomposites made with pulsed current, the wear rate does not change much as the number of particles with current density increases. This is explained by the coating’s higher particle count, which reduces its plastic deformation property and causes failure by creating microcracks [42]. The impact of pulsed current density on micro-hardness, wear characteristics, relative texture coefficient and microstructure of Ni-TiN was examined by F. Xia et al. [51]. A Ra value of 29.57 nm indicates that the Ni-TiN coating produced at 60 mA/cm2 had the most compact and smooth surface morphology of all the coatings. The coating created at 60 mA/cm2, however, has the lowest friction coefficient, wear loss, and greatest micro-hardness value.
3.2.2. Current Type
3.2.3. Pulse Frequency
3.2.4. Duty Cycle
- A longer dwell time (i.e., a lower duty cycle) increases the chances of nanoparticles reaching the cathode surface;
- Due to this longer dwell time, weakly adsorbed particles may detach due to hydrodynamic forces;
- Nanoparticles on the cathode surface are more likely to be incorporated into the coating if the dwell period is shortened (i.e., the duty cycle is increased);
- A shorter stay period lowers the concentration of nanoparticles since it is less likely that they will reach the cathode surface.
3.3. Hydrodynamics and Agitation
3.3.1. Mechanical Agitation
3.3.2. Ultrasonic Agitation
3.3.3. Electrolyte Circulation
3.3.4. Magnetic Field
3.3.5. Electrodeposition by Jet
3.4. Bath Composition (Temperature, Surfactant, pH, Composition, Additives)
3.4.1. Temperature
3.4.2. Surfactant
3.4.3. pH
3.4.4. Additives
3.4.5. Other Electroplating Solution
4. Industrial Applications
5. Gaps in Current Research and Future Prospects
5.1. Analysis of Current Challenges
- Influence of Surface Topography on Mechanical Measurements: Surface topography is a key factor in interpreting microhardness measurements. The incorporation of nanoparticles often leads to increased roughness, which can disrupt indentation tests by altering contact conditions. In particular, SiC and Al2O3 particles, while contributing to increased hardness, generate local asperities that can increase the dispersion of measured values. The results of this study confirm that higher roughness is associated with greater variability in hardness (HV) values, thus highlighting the need to consider surface topography when analyzing and comparing the mechanical properties of nanocomposite coatings.
- Variability of Experimental Protocols: Tribological properties such as the coefficient of friction (CoF) and the wear rate (Ws) are highly sensitive to test conditions: applied load, sliding speed, temperature, and counterbody material. Comparing results between studies is difficult due to the diversity of methods. The normalized wear rate presented in this study allows for a more consistent comparison, revealing consistent trends: hard particles improve wear resistance while solid lubricants reduce the CoF, in agreement with the literature [16,18,19].
- Discrepancy between theoretical models and real-world conditions: Theoretical models often assume idealized conditions that do not reflect the complexity of real-world electrodeposition processes. Our results show that discrepancies arise due to particle agglomeration, bath instability, and local current density variations. Multiphysics simulations and advanced optimization tools (RSM, AI, ML) are essential for more reliably predicting particle incorporation.
- Environmental and Health Considerations: Electrodeposition processes involving nickel and other heavy metals present significant environmental and health risks due to the presence of metal ions, chemical additives, acid emissions, and persistent surfactants. Beyond performance optimization, particular attention must be paid to bath lifespan and reconditioning to reduce chemical consumption and waste generation. Effective waste management strategies are essential to limit the release of metal ions, nanoparticles, and organic additives during bath renewal or disposal. Furthermore, the environmental fate of persistent surfactants and additives remains a major concern, as their accumulation can lead to long-term ecological risks. The results of this study suggest that optimizing deposition parameters and particle selection not only improves coating performance but also contributes to more sustainable and environmentally friendly electrodeposition practices.
5.2. Research Perspectives
- Particle Dispersion and Bath Stability: Detailed studies on particle electrophoresis, the effect of surfactants, and bath aging are necessary to ensure uniform incorporation and coating consistency.
- In situ characterization: Techniques such as in situ absorption spectroscopy and cross-sectional profilometry can shed light on particle adsorption dynamics and crack propagation, improving our understanding of coating formation mechanisms.
- Advanced modeling and optimization: The integration of multi-physics models with DoE, AI, and ML approaches will enable the identification of optimal parameter combinations while taking into account bath composition, electrode geometry, agitation, and particle concentration.
- Durability under dynamic and cyclic loads: Future studies should evaluate long-term performance under realistic service conditions, including high-pH environments and cyclic mechanical stresses, to ensure the robustness of the matrix–particle interface.
- Comparative framework and design selector: The creation of a “design selector” for the different composite coatings will make it possible to choose the optimal deposits according to the applications while considering aging, maintenance and environmental impact.
6. Conclusions
- Depending on the type of particle, the results indicate that adding particles to the nickel matrix improves the coatings’ wear resistance and surface characteristics. Lubricants with superior wear resistance can be produced using composite coatings, depending on the kind of particles utilized in wear tests. Hard particles like oxides and carbides are coated with composites that are very resistant to wear.
- The volume proportion of these particles thereby affects the coating’s ductility. In harsh wear circumstances, material removal is slowed down by increasing the composition of the reinforcing phase because the latter resists plastic deformation and offers superior protection to the nickel matrix. Nevertheless, when the proportion of reinforcing particles rises to a sufficient level (over 50 vol. %), the metal matrix functions as a binder, strengthening the ceramic particles. Here, the composite’s wear behavior is comparable to that of hard particles.
- By altering the electrochemical conditions and the material’s mobility in the electrolysis bath, external fields can change the geometry of the metal matrix and the co-deposition of particles. In comparison to Ni deposition under the same DC circumstances, recent investigations have demonstrated that the final material qualities (hardness, wear resistance, corrosion resistance, tribological properties, etc.) of Ni deposition by PC plating were superior. Superior final material properties are demonstrated by the PC-plated nanocomposite coatings at low duty cycle and low pulse frequency compared to the identical DC circumstances.
- Bath agitation (USED, MESED, CED, MASED, MAPED, JTED) is an important source of external energy that affects material transport even though it is not a “field” in the traditional sense.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
| ALS | Ammonium lignosulfonate |
| ANOVA | Analysis of variance |
| ANN | Artificial neural networks |
| BP | Back Propagation |
| CCD | Central composite design |
| CoF | Coefficient of friction |
| CSD | Circulating-solution electrodeposition |
| CVD | Chemical Vapor Deposition |
| DES | Deep eutectic solvent |
| DLC | Diamond-Like Carbon |
| FEM | Finite element method |
| GRA | Grey relation analysis |
| JED | Jet Electrodeposition |
| JMED | Jet magnetic electroplating |
| IBAD | Ion Beam-Assisted Deposition |
| MAPED | Magnetically assisted pulse electrodeposition |
| MASED | Magnetic stirring electrodeposition |
| MESED | Mechanical stirring electrodeposition |
| MHD | Magneto-hydrodynamic |
| MMC | Metal matrix composites |
| PS | Probe sonication |
| PVD | Physical Vapor Deposition |
| ROM | Rule of mixtures |
| RSM | Response surface methodology |
| SHMP | Sodium hexametaphosphate |
| SLS | Sodium dodecyl sulfate |
| USED | Ultrasonic electrodeposition |
| DC | Direct current |
| PC | Positive pulsed current |
| PNPC | Positive-negative pulsed current |
Symbols
| V | Volume loss |
| CW | Volumetric wear |
| Ar | Real contact area |
| Shear strength | |
| F | Load |
| S | Sliding distance |
| Coefficient of friction | |
| Total coefficient of friction | |
| Adhesional coefficient of friction | |
| Deformational coefficient of fraction | |
| F | Frictional force |
| W | Normal force |
| Adhesional force | |
| Deformational force | |
| Q | Wear volume in mm3 |
| W | Vertical load applied in kgf |
| Ws | Specific wear rate in mm3/N-m |
| L | Sliding distance in mm |
| H | Hardness in kgf.mm3 |
| Hup | Hardness upper bound |
| Hlow | Hardness for lower bound |
| Hr | Hardness for reinforcement |
| Hm | Hardness for matrix |
| fr | Volume fraction for reinforcement |
| fm | Volume fraction for matrix |
| P | Maximum force of indentation |
| A | Projected area of the indent |
| Hardness | |
| d | Grain size |
| Intrinsic resistance of the material | |
| k | material-dependent constant |
| he | Depth of elastic recovery |
| hmax | Maximum depth |
| Er | Reduced Young’s modulus |
| CT | Coating thickness in μm |
| HV | Microhardness in VHN |
| TF | Scratch test in N |
| UTS | Tensile strength in N/mm2 |
| Ra | Roughness in μm |
| MW | Mass loss due to wear in g |
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| Coatings | Ni | Ni-SiC | Ni-SiC-Graphite | Graphite | |
|---|---|---|---|---|---|
| Particle content Vol. | 0 | 1.58 ± 0.48 | 1.45 ± 0.51 | 5.32 ± 1.5 | 3.99 ± 0.48 |
| Particle content Wt. | 0 | 0.58 ± 0.18 | 0.55 ± 0.2 | 1.41 ± 0.42 | 1.03 ± 0.13 |
| Micro hardness (HV) | 262 ± 5 | 370 ± 25 | 360 ± 50 | 300 ± 10 | |
| CoF | 0.15 ± 0.1 | 0.22 ± 0.1 | 0.19 ± 0.1 | 0.14 ± 0.1 | |
| Wear factor 10−4 (mm3/N·m) | 80 ± 25 | 55 ± 5 | 52 ± 5 | 70 ± 5 | |
| Particle Size | Hardness (HV) | Indentation Depths (μm) | Wear Mass Loss (mg) |
|---|---|---|---|
| Small | 870 ± 30 | 15 ± 3 | 35 ± 2 |
| Medium | 750 ± 10 | N.R | 56 ± 3 |
| Large | 570 ± 20 | 23 ± 2 | 73 ± 3 |
| Particle Concentration | Depth of Worn Scratch | Width of Worm Scratch | CoF |
|---|---|---|---|
| 1 g/L | 53 μm | 631.2 μm | ~1.03 |
| 2 g/L | 49 μm | 567.9 μm | NR |
| 4 g/L | 45 μm | 504.8 μm | NR |
| 8 g/L | 30 μm | 441.7 μm | NR |
| 16 g/L | 18 μm | 378.6 μm | ~0.73 |
| Sample | Crain Area (μm2) | Roughness Ra (μm) | Microhardness HV | Reduced Young’s Modulus Er (GPa) | CoF | Volumetric Wear Factor ×10−4 (mm3/Nm) |
|---|---|---|---|---|---|---|
| Ni | 7.21 ± 0.27 | 0.27 ± 0.04 | 270 ± 28.41 | 170.45 ± 5.86 | ~0.15 | ~62 |
| Ni-SiC | 4.24 ± 0.3 | 0.32 ± 0.07 | 448 ± 35.27 | 197.32 ± 9.99 | ~0.37 | ~34 |
| Ni-MoS2 | <0.02 | 0.74 ± 0.11 | 446 ± 112.48 | 173.47 ± 8.62 | ~0.06 | ~10 |
| Ni-SiC-MoS2 | <0.02 | 0.73 ± 0.06 | 1110 ± 200.49 | 219.70 ± 18.56 | ~0.07 | ~5 |
| Sample | Plating Current Type | Microhardness HV | Wear Loss (mg) | CoF | Interface Binding Force (MPa) |
|---|---|---|---|---|---|
| 1 | DC | 317.4 | 9.2 | ~0.71 | 380.7 |
| 2 | PC | 381.1 | 3.1 | ~0.5 | 851.9 |
| 3 | PRC | 490.4 | 1.7 | ~0.38 | 1047.1 |
| Sample | Magnetic Intensity (T) | Magnetic Direction | Ra (nm) | Microhardness (HV) | Wear Rate (mg/min) | CoF |
|---|---|---|---|---|---|---|
| MS0 | 0 | - | 147 | 653.7 | 0.42 | 0.68 |
| MS1 | 0.4 | Perpendicular | 76 | 914.8 | 0.18 | 0.29 |
| MS2 | 04 | Parallel | 125 | 761.4 | 0.26 | 0.51 |
| Sample | Nozzle Diameters (mm) | Microhardness (HV) | CoF | Wear Loss (mg) |
|---|---|---|---|---|
| 1 | 468 | 28.6 | 0.518 | |
| 2 | ~525 | ~24 | 0.437 | |
| 3 | 647 | 17.3 | 0.312 | |
| 4 | 493 | 21.1 | 0.376 |
| Combination | Jet Rate (m/s) | Al2O3 Content (g/L) | Ultrasonic Power (W) | Microhardness (HV) | CoF | Wear Extent (mg) |
|---|---|---|---|---|---|---|
| G1 | 4 | 15 | 200 | 713.7 | 0.54 | 10.84 |
| G2 | 3.71 | 15.38 | 210 | 724.9 | 0.41 | 8.61 |
| G3 | 3 | 15 | 250 | 683.4 | 0.62 | 9.67 |
| Study | Method | Nanoparticles | Key Deposition Parameters | Microhardness (HV) | CoF | Wear Rate (Ws) | Reference |
|---|---|---|---|---|---|---|---|
| A: Refining the optimized conditions by the extended Taguchi method on dry sliding wear behavior | Taguchi | Al2O3 | 40 °C, 1,75 A/dm2 et 4,5 g/L | 0.06991 mm3/N-m | [16] | ||
| B: Developing an empirical relationship between: Input parameters: f (Hz), η (%), i (A/cm2) and Output parameters: Hv, Ra, Ws, CoF | RSM + GRA | Al2O3 | 34 °C; 1 A/dm2, 1.2 g/L | 350.3 VHN | 0.1785 mm3/N-m | [18] | |
| C: Developing an empirical relationship between: Input parameters: f (Hz), η (%), i (A/cm2) and Output parameters: Hv, Ra, Ws, CoF | RSM + GRA | SiC | 10 Hz; 10%; 0.2 A/cm2 | 337.8 VHN | 0.36 | 0.0001005 mm3/N-m | [19] |
| D: Optimizing the electrodeposition parameters for Ni-Al2O3 composite coatings using the Taguchi method: Input parameters: ω (200–350 rpm), i (2–5 A/cm2), C (10–25 g/L), deposition period (15–60 min) and Output parameter: Hv, average crystalline size (nm), incorporated alumina (wt.%). | Taguchi | Al2O3 | 4 A/dm2, 15 g/L, 60 min, 300 rpm | 712 HV | [95] | ||
| E: A backpropagation neural network (BP-NN) with a 3 × 8 × 1 structure was used to predict the wear resistance of Ni-SiC nanoparticles deposited electrochemically using ultrasound. Input parameters: T (20–60 °C), i (0.5–3 A/cm2), C (2–10 g/L) and Output parameter: W (mg), CoF | BP-NN | SiC | 8 g/L, 2 A/dm2, 40 °C | [96] |
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Abdesselam, Y.; Tampu, C.; Belloufi, A.; Rezgui, I.; Abdelkrim, M.; Chirita, B.; Herghelegiu, E.; Schnakovszky, C.; Tampu, R. Optimization of the Effects of Electrodeposition Parameters on the Nickel-Based Composite Coatings’ Tribological Properties. Processes 2026, 14, 139. https://doi.org/10.3390/pr14010139
Abdesselam Y, Tampu C, Belloufi A, Rezgui I, Abdelkrim M, Chirita B, Herghelegiu E, Schnakovszky C, Tampu R. Optimization of the Effects of Electrodeposition Parameters on the Nickel-Based Composite Coatings’ Tribological Properties. Processes. 2026; 14(1):139. https://doi.org/10.3390/pr14010139
Chicago/Turabian StyleAbdesselam, Yassine, Catalin Tampu, Abderrahim Belloufi, Imane Rezgui, Mourad Abdelkrim, Bogdan Chirita, Eugen Herghelegiu, Carol Schnakovszky, and Raluca Tampu. 2026. "Optimization of the Effects of Electrodeposition Parameters on the Nickel-Based Composite Coatings’ Tribological Properties" Processes 14, no. 1: 139. https://doi.org/10.3390/pr14010139
APA StyleAbdesselam, Y., Tampu, C., Belloufi, A., Rezgui, I., Abdelkrim, M., Chirita, B., Herghelegiu, E., Schnakovszky, C., & Tampu, R. (2026). Optimization of the Effects of Electrodeposition Parameters on the Nickel-Based Composite Coatings’ Tribological Properties. Processes, 14(1), 139. https://doi.org/10.3390/pr14010139

