In-situ formation of SrCO3 microcrystals-decorated Fe3O4 nanosheets as an efficient and long-lasting catalyst for overall water splitting
Bibliographic record
Abstract
• Hydrothermal synthesis enabled in-situ Fe 3 O 4 @SrCO 3 /NF formation with enhanced surface roughness and stability. • Catalytic performance surpassed commercial IrO 2 /NF with 243 mV OER overpotential and a low Tafel slope of 38 mV dec −1 . • DFT calculations revealed in-situ formed SrCO 3 lowers the OER energy barrier to 0.73 eV, optimizing charge redistribution. • Fe 3 O 4 @SrCO 3 /NF demonstrated outstanding stability, maintaining OER for 300 h and OWS for 125 h at 10 mA cm −2 . A novel Fe 3 O 4 @SrCO 3 /NF electrocatalyst material was developed via hydrothermal synthesis, creating a composite structure with Fe 3 O 4 nanosheets and SrCO 3 crystals on nickel (Ni) foam (NF) that enhances surface roughness and stability, in turns optimizing catalytic performance in water-splitting applications. In 1.0 M KOH, the as -prepared Fe 3 O 4 @SrCO 3 /NF achieved a low OER overpotential of 243 mV at 10 mA cm −2 , surpassing commercial IrO 2 /NF, with a Tafel slope of 38 mV dec −1 indicating rapid reaction kinetics. Electrochemical Impedance Spectroscopy (EIS) confirmed a low charge transfer resistance ( R ct ) of 1.49 Ω, indicating efficient electron mobility. For HER, Fe 3 O 4 @SrCO 3 /NF displayed a moderate overpotential of 172 mV at − 10 mA cm −2 . In a two-electrode setup with Pt/C (cathode), Fe 3 O 4 @SrCO 3 /NF (anode) demonstrated efficient overall water splitting, requiring only 1.55 V at 10 mA cm −2 , underscoring its viability for sustainable energy applications. Density Functional Theory (DFT) calculations revealed that SrCO 3 in-situ formation not only shifted the OER rate-determining step, lowering the energy barrier to 0.73 eV, but also optimized the d -band center and facilitated interfacial charge redistribution, enhancing intermediate adsorption and catalytic activity. Notably, Fe 3 O 4 @SrCO 3 /NF demonstrated exceptional stability, sustaining OER activity for over 300 h and delivering stable overall water-splitting performance for 125 h, significantly outperforming many state-of-the-art OER catalysts. This durability, combined with high catalytic efficiency, establishes Fe 3 O 4 @SrCO 3 /NF as a promising candidate in non-precious metal electrocatalysts for water-splitting technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".