Hierarchical Chestnut-Burr Like Structure of Copper Cobalt Oxide Electrocatalyst Directly Grown on Ni Foam for Anion Exchange Membrane Water Electrolysis
Bibliographic record
Abstract
Uniquely nanostructured CuCo 2 O 4 is presented as an electrocatalyst for oxygen evolution reactions (OER). CuCo 2 O 4 particles in a chestnut-burr-like shape (CCO*, where ∗ = chestnut burr) were hydrothermally synthesized around fibers of Ni foam substrates as current collectors. Chestnut burrs 4 μm on average had thorns consisting of less than five threads. Each thread was made of a consecutive array of nanobeads less than 10 nm. Nanovoids or nanopores were found between nanobeads. The chestnut-burr structure of CCO* allowed IrO 2 -overwhelming OER activity. By using the hierarchically nanostructured electrocatalyst directly grown on current collectors without binders and conducting agents, high performances of anion exchange membrane (AEM) electrolysis was demonstrated. Three merits of the electrode architecture were emphasized. First, mass transfer pathways for reactants and products were secured in a microscale between thorns and in a nanoscale between nanobeads. Second, more active sites were exposed to electrolytes in the hierarchical structure. Third, direct growth of active materials on conductive substrates improved adhesion and electrical conduction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".