Orbital Occupancy Modulation to Optimize Intermediate Absorption for Efficient Electrocatalysts in Water Electrolysis and Zinc–Ethanol–Air Battery
Bibliographic record
Abstract
Abstract Spin engineering is a promising way to modulate the interaction between the metal d‐orbital and the intermediates and thus enhance the catalytic kinetics. Herein, an innovative strategy is reported to modulate the spin state of Co by regulating its coordinating environment. o‐c‐CoSe 2 ‐Ni is prepared as pre‐catalyst, then in situ electrochemical impedance spectroscopy (EIS) and in situ Raman spectroscopy are employed to prove phase transition, and CoOOH/Co 3 O 4 is formed on the surface as active sites. In hybrid water electrolysis, the voltage has a negative shift, and in zinc–ethanol–air battery, the charging voltage is lowered and the cycling stability is greatly increased. Coordinated atom substitution and crystalline symmetry change are combined to regulate the absorption ability of reaction intermediates with balanced optimal adsorption. Coordinated atom substitution weakens the adsorption while the crystalline symmetry change strengthens the adsorption. Importantly, the tetrahedral sites are introduced by Ni doping which enables the co‐existence of four‐coordinated sites and six‐coordination sites in o‐c‐CoSe 2 ‐Ni. The d z 2 + d x 2 ‐y 2 orbital occupancy decreases after the atomic substitution, while increases after replacing the CoSe 6 ‐O h field with CoSe 6 ‐O h /CoSe 4 ‐T d . This work explores a new direction for the preparation of efficient catalysts for water electrolysis and innovative zinc–ethanol–air battery.
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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".