Sense Mametja, Olga K. Mmelesi, Liberty L. Mguni, Joshua Gorimbo, Xinying Liu
For water splitting, nickel-based layered double hydroxides (Ni-LDHs) have become the most popular non-precious catalysts. Ni-based LDHs application in electrocatalysis (EC) has been studied the most, followed by photocatalysis (PC) and photoelectrochemistry (PEC). Particularly for the oxygen evolution reaction, their layered structure, variable composition, and special redox-active Ni²⁺/Ni³⁺ pair allow for exceptional catalytic performance. Although defect engineering, dominated by oxygen vacancies and heteroatom doping, is still relatively immature, heterostructure generation is the strategy that has been investigated the most among those aimed at increasing Ni-LDH activity. Both machine learning (ML) and density functional theory (DFT), which are still in their infancy, have been used in recent work to help direct catalyst design. The lack of scalable synthesis pathways is a significant obstacle to practical implementation, as the large-scale manufacturing of Ni-LDHs has not yet been proven. In order to entirely realise the potential of Ni-LDHs for sustainable hydrogen production, this review outlines recent developments, emphasises the maturity of EC in comparison to PC and PEC, and identifies research gaps in defect engineering, computational modelling, and industrial-scale synthesis.