The development of platinum group metal free (PGM-free) electrocatalysts is essential to progress towards affordable oxygen reduction reaction (ORR). In this work, Ni-W nanoparticles (NPs) were electrodeposited on carbon cloth (CC) under both direct current and pulsed conditions from a gluconate-based electrolyte [1]. Machine learning (ML) was employed to identify the optimal deposition parameters for enhancing ORR performance in alkaline medium. The variables tuned during NP synthesis included temperature, overpotential, deposition time, and the rotation speed of the electrode, the latter controlled using a rotating disk electrode (RDE) to regulate mass transport.

For the electrochemical characterization, 200 cyclic voltammetries were performed in 0.1 M KOH on a three-electrode cell configuration with a RDE as the working electrode. The key parameters used to evaluate the catalytic activity and durability of the NPs were the half-wave potential and overpotential, both measured at the first and last cycles.

The morphology of the deposited NPs was examined by SEM to determine particle distribution across the CC substrate and particle size, which ranged from 40 nm to 600 nm depending on the deposition conditions. High-resolution (S)TEM imaging was conducted to elucidate the crystal structure and atomic distribution of Ni and W within the NPs. The analysis revealed that W preferentially accumulates towards the surface of the NPs, a feature that contributes to enhanced stability during ORR.

This work is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible for them.

[1] R. de Paz-Castany et al. ChemSusChem 18 (2025) e202400444.