Experimental design for modelling and multi-response optimization of Fe–Ni electroplating process

Morphology study of zinc anode prepared by electroplating method for rechargeable Zn-MnO2 battery

Zinc electrodes prepared by electrodepositing zinc on a copper plate in ZnSO₄ electrolyte were studied to determine the most suitable condition of zinc anode preparation for high performance Zn-MnO₂ battery. Deposition of zinc on substrate material was confirmed using X-ray diffraction (XRD) measurement. Morphological characterization of zinc anode was performed by scanning electron microscopy (SEM). It was observed that concentration of electrolyte and electrical current density influenced the morphology of zinc electrode. At 1 M ZnSO₄ and current density values of 0.06–0.1 A/cm², it was found that the morphological structure of zinc electrode was orderly arranged in a layer-by-layer structure. This indicated that the current density played an important role on deposition morphology and even on the crystal structure. Performance of electrodes was tested by a battery analyzer for 100 cycles. The results of the tests showed that the electrode with the layer-by-layer morphology yielded a high efficiency of up to 99.97% which was higher and more stable than those of the electrodes with disordered and scattered morphology. The layer-by-layer morphology is therefore a key factor for improving the performance of Zn-MnO₂ cell.

Using the Multi-Response Method with Desirability Functions to Optimize the Zinc Electroplating of Steel Screws

Zinc electroplating is a coating process controlled by several input process parameters. However, the commonly used input parameters for setting the process of zinc deposition are current density, temperature of the coating solution, zinc concentration, deposition time, and concentration of additives (conditioner and brightener). The power consumed in the zinc plating process, coating thickness, increase in coating mass, and corrosion resistance are considered to be outputs or zinc coating parameters. They are widely used when the zinc coating requirements are based on the coating process cost, coating process speed, corrosion resistance, and coating thickness. This paper seeks to determine regression models by the response surface method (RSM) that relate the zinc coating parameters to the input parameters in steel screws. When considering the coating requirements of cost, coating process speed, corrosion resistance, and coating thickness, the optimal input parameters were found by using a multi-response surface (MRS). Input parameters of 0.3 amps/dm2, 20.0 °C, 13.9 g/L, 45 min, 28.5 mL/L, and 2.8 mL/L, respectively (relative to the commonly used input parameters detailed above), were obtained when considering the cost. Considering minimization of the deposition time, the input parameters obtained were 0.5 amps/dm2, 24.6 °C, 13.9 g/L, 45 min, 26.9 mL/L, and 1.1 mL/L, respectively. The optimal inputs to maximize the corrosion resistance were 0.6 amps/dm2, 32.4 °C, 14.0 g/L, 45 min, 28.7 mL/L, and 2.5 mL/L, respectively. Finally, when maximizing the coating thickness, the inputs were 0.7 amps/dm2, 38.4 °C, 12.2 g/L, 45 min, 26.5 mL/L, and 1.5 mL/L, respectively.