Replication data for "Hydrogen Evolution Reaction of Electrodeposited Ni-W Films in Acidic Medium and Performance Optimization Using Machine Learning"

Experimental raw data for all figures presented in the paper "Hydrogen Evolution Reaction of Electrodeposited Ni-W Films in Acidic Medium and Performance Optimization Using Machine Learning" are provided. The data were utilized to investigate and optimize the electrodeposition conditions of Ni-W films for hydrogen evolution reaction (HER) using machine learning. The study began with an analysis of bath and electrodeposition conditions (Figure 1), followed by SEM imaging of the film morphologies at several current densities and temperatures (Figure 2). The crystal structure of the films was characterized by GIXRD (Figure 3), and the electrocatalytic properties were tested (Figures 4, 5). Additionally, the durability of the films in acidic media was assessed (Figures 6, 7). Subsequently, machine learning was employed to optimize the deposition conditions (ML data). The best-performing samples were further analysed using SEM, TEM, electrochemical measurements (Figures 8, 9), XPS (Figure 11), and XRD (Figure 12) to evaluate the optimized film properties both before and after HER testing.