Decoding linker contributions in solid state synthesis of MOF-derived NiCo2O4/NiO/C composites for efficient electrocatalytic OER: Machine learning assisted prediction and forecasting of device stability

초록

Background: Electrolytic water splitting is crucial as it produces hydrogen; a clean, renewable energy source, and oxygen, using electricity that can potentially come from sustainable sources, thereby assisting to lessen greenhouse gas emissions and reliance on fossil fuels. Methods: Herein, we report innovative in-situ synthesis of NiCo2O4 composite with NiO and carbon (NCN@C) for electrocatalytic oxygen evolution reaction (OER). A new solid-state synthesis approach is presented, involving mechanical grinding of separately prepared Ni and Co-MOFs, followed by pyrolysis to obtain a highly efficient NCN@C catalyst. The choice of MOFs with different organic linkers plays a crucial role in achieving a nonagglomerated distribution of the NiCo2O4/NiO system on the carbon matrix. Significant findings: The NCN@C composite showed the lowest OER overpotential of 294 mV at 10 mA cm-2 among all tested samples. The NCN@C || NCN@C electrolyzer cell demonstrated overall water splitting at 1.58 V with exceptional stability. Additionally, the stability of the electrolyzer was evaluated, modeled and predicted using a machine learning-driven long short-term memory (LSTM) algorithm.

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