Single‐atomic Co‐B<sub>2</sub>N<sub>2</sub> sites anchored on carbon nanotube arrays promote lithium polysulfide conversion in lithium–sulfur batteries
Bibliographic record
Abstract
Abstract Due to low cost, high capacity, and high energy density, lithium–sulfur (Li–S) batteries have attracted much attention; however, their cycling performance was largely limited by the poor redox kinetics and low sulfur utilization. Herein, predicted by density functional theory calculations, single‐atomic Co‐B2N2 site‐imbedded boron and nitrogen co‐doped carbon nanotubes (SA‐Co/BNC) were designed to accomplish high sulfur loading, fast kinetic, and long service period Li–S batteries. Experiments proved that Co‐B2N2 atomic sites can effectively catalyze lithium polysulfide conversion. Therefore, the electrodes delivered a specific capacity of 1106 mAh g−1 at 0.2 C after 100 cycles and exhibited an outstanding cycle performance over 1000 cycles at 1 C with a decay rate of 0.032% per cycle. Our study offers a new strategy to couple the combined effect of nanocarriers and single‐atomic catalysts in novel coordination environments for high‐performance Li–S batteries.
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) | 0.001 | 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".