Hollow Multivoid Nanocuboids Derived from Ternary Ni–Co–Fe Prussian Blue Analog for Dual‐Electrocatalysis of Oxygen and Hydrogen Evolution Reactions
Bibliographic record
Abstract
Abstract Hydrogen generation from electrochemical water‐splitting is an attractive technology for clean and efficient energy conversion and storage, but it requires efficient and robust non‐noble electrocatalysts for hydrogen and oxygen evolution reactions (HER and OER). Nonprecious transition metal–organic frameworks (MOFs) are one of the most promising precursors for developing advanced functional catalysts with high porosity and structural rigidity. Herein, a new transition metal‐based hollow multivoid nanocuboidal catalyst synthesized from a ternary Ni–Co–Fe (NCF)‐MOF precursor is rationally designed to produce dual‐functionality toward OER and HER. Differing ion exchanging rates of the ternary transition metals within the prussian blue analog MOF precursor are exploited to produce interconnected internal voids, heteroatom doping, and a favorably tuned electronic structure. This design strategy significantly increases active surface area and pathways for mass transport, resulting in excellent electroactivities toward OER and HER, which are competitive with recently reported single‐function nonprecious catalysts. Moreover, outstanding electrochemical durability is realized due to the unique rigid and interconnected porous structure which considerably retains initial rapid charge transfer and mass transport of active species. The MOF‐based material design strategy demonstrated here exemplifies a novel and versatile approach to developing non‐noble electrocatalysts with high activity and durability for advanced electrochemical water‐splitting systems.
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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) | 0.000 | 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 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".