Two-Dimensional Phosphorus-Doped Carbon Nanosheets with Tunable Porosity for Oxygen Reactions in Zinc-Air Batteries
Bibliographic record
Abstract
Large-sized two-dimensional phosphorus-doped carbon nanosheets (2D-PPCN) with tunable porosity were synthesized via a multifunctional templating method. A single inexpensive solid precursor, phosphorus pentoxide, is combined with common saccharides in a stepwise multiple templating process for 2D construction, phosphorus doping, and regulated micro-/mesopore creation. This reliable 2D porous carbon production technique can potentially be utilized in a variety of energy storage and conversion fields. The effects of different porous structures on the electrocatalytic activity of 2D-PPCN based electrocatalysts are specifically investigated in this work. The interconnected open-pore system and high specific surface area result in a high catalytic efficiency for both the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). When integrated into an air-breathing cathode for rechargeable Zn-air batteries, the best-performing 2D-PPCN demonstrates better cell performance than a noble metal benchmark catalyst and a higher durability with over 1000 charge–discharge cycles.
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".