Dealloying Ni-Co-Se Electrocatalysts for Efficient and Stable Oxygen Evolution at High Current Densities
Bibliographic record
Abstract
Stable and affordable electrocatalysts are urgently needed to accelerate the transition from conventional fossil fuels to sustainable energy resources such as solar and wind. Over the last two decades, the electrocatalytic splitting of water, and carbon dioxide reduction to hydrocarbons have received great attention, however approximately 90% of the electricity input is consumed at the anodic oxygen evolution reaction (OER) due to poor reaction kinetics. Precious metal-based electrocatalysts (Pt, Ir, Ru) have been commonly used as OER catalysts, but proven uneconomic for large scale industrial deployment. First-row transition metal elements (Ni, Co, Fe) offer a great earth abundant and low-cost alternative for OER. In this work, we used a two-step novel milling process to produce Ni,Co-based nanocrystalline electrocatalysts. Cryo-milling (mechanical milling of precursors at cryogenic temperatures to achieve alloying) followed by surfactant-assisted ball milling (SABM), to reduce particles to nanoparticle, create stable disordered phases with high surface areas and coordinatively unsaturated active sites for the reaction of OER intermediates. Two Ni-Co-Se alloys were milled under various conditions and the structural evolution of the systems was monitored using X-ray diffraction (XRD) and electron microscopy. Our results confirmed the production of two fully alloyed ternary systems (NiCo)3Se4 and (NiCo)Se after 6 hours of milling time. The electrocatalytic activity and stability of the catalysts were evaluated by Tafel measurements obtained from linear sweep voltammetry (LSV) and cyclic voltammetry (CV) experiments. We found that Se in NiCo-based alloys stabilized the disordered structure by forming non-transitional clusters and significantly facilitated the production of nanoparticles. In situ X-ray Absorption Spectroscopy (XAS) and electron microscopy revealed that Se was dealloyed during the OER reaction activating the electrocatalysts by facilitating the formation of active Ni-Co oxyhydroxides. On a glassy carbon electrode at 10 mA.cm-2, activated (NiCo)3Se4 demonstrated a stable performance for 500 hours at 268 mV overpotential with a Tafel slope of 42 mV.dec-1. Moreover, the the catalyst was stable for 100 hours while delivering 500 mA.cm-2 at 320 mV of overpotential. This work suggests that milling can potentially be used to produce OER catalysts for industrial application.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".