Hydrogen Evolution Reaction of Electrodeposited Ni-W Films in Acidic Medium and Performance Optimization Using...

Area of Science:

• Electrochemistry
• Materials Science
• Surface Science

Background:

• Nickel-Tungsten (Ni-W) alloys are investigated for catalytic applications.
• Surface morphology significantly impacts the electrocatalytic activity of Ni-W films.
• Optimizing electrodeposition parameters is crucial for enhancing material performance.

Purpose of the Study:

• To investigate the effect of electrodeposition parameters on Ni-W alloy film properties.
• To correlate surface morphology with hydrogen evolution reaction (HER) activity.
• To utilize machine learning for predicting optimal deposition conditions for enhanced HER performance.

Main Methods:

• Electrodeposition of Ni-W alloy films from a gluconate bath at varying current densities and temperatures.
• Electrochemical characterization using linear sweep voltammetry (LSV) in sulfuric acid.
• Application of a machine learning algorithm to predict optimal deposition parameters.

Main Results:

• Ni-W films (~12 at.% W) exhibited morphology-dependent HER activity.
• Optimal performance was achieved at a current density of -4.8 mA/cm² and 50°C.
• Machine learning predicted conditions yielded Ni-W films with improved Tafel slopes (33-45 mV/dec) and low overpotentials (0.09-0.10 V).

Conclusions:

• Surface morphology is a key factor in the HER activity of Ni-W alloy films.
• Machine learning effectively predicts optimal electrodeposition parameters for enhanced catalytic performance.
• The optimized Ni-W films demonstrate superior stability and efficiency for HER applications.