Potential-dependent reconstruction of Ni-based cuboid arrays for highly efficient hydrogen evolution coupled with electro-oxidation of organic compound

• Ni@O-Ni pre-electrocatalyst with porous and O-riched surface was in-situ prepared. • Ni@O-Ni undergoes self-reconstruction processes to generate actual active sites. • Ni@Ni/NiO x and Ni@Ni/NiO x were fabricated via cathodic/anodic activation processes. • Ni@Ni/NiO x shows a low overpotential of 71 mV to reach 10 mA cm −2 for HER. • Ni@NiO x exhibits a yield (∼99%) of Ph-COOH product for Ph-CH 2 OH electro-oxidation. In-situ surface self-reconstruction of electrocatalysts plays a crucial role in efficiently catalyzing the hydrogen evolution reaction (HER) and the organic compound oxidation reaction. Herein, a core@shell structure of metallic Ni@O-riched Ni layer (Ni@O-Ni) pre-electrocatalyst was established, which possesses a unique self-adaptable ability for the potential-dependent reconstruction to generate actual active sites for catalytic reactions. The reconstructed Ni@Ni/NiO x during the cathodic activation process shows an outstanding HER activity with a low overpotential of 71 mV to reach 10 mA cm −2 and remarkable stability in 1.0 M KOH. In addition, the core@shell structured Ni@NiO x during the anodic activation process contributes to abundant redox reactions for the electro-oxidation of organic compound. Especially, the Ni@NiO x exhibits an ultralow potential of 1.309 V at 10 mA cm −2 and ∼99% yield of benzoic acid (Ph-COOH) product for the electro-oxidation reaction of benzyl alcohol (Ph-CH 2 OH). In-situ Raman spectra corroborate the reversible transformation of Ni 2+ - O x and γ-Ni 3+ - OOH and reveal the vital role of γ-Ni 3+ - OOH in seizing the proton for Ph-CH 2 OH electro-oxidation reaction. Moreover, the constructed integrated water splitting coupled with Ph-CH 2 OH electro-oxidation needs only a cell voltage of 1.438 V at 10 mA cm −2 , resulting in an electrical energy saving of 14.3% compared to overall water splitting. This work proposes profound insights into the correlation between surface features, potential-dependent reconstruction, and the multifunctionality of electrocatalysts.