CO<sub>2</sub>-Derived Hierarchical Porous Carbon Electrode and Interlayer Doped with Nitrogen for Lithium-Sulfur Battery
Bibliographic record
Abstract
Shuttle phenomena of lithium polysulfides (LiPSs) in lithium sulfur (Li-S) batteries is a serious obstacle to commercialization of Li-S battery. Various studies are being conducted to mitigate the shuttle effect, but among them, the approach using an interlayer has been introduced. This study proposes a hierarchical carbon material for both carbon cathode composite and interlayer synthesized from gaseous carbon dioxide. The highly porous carbon material used as a cathode enables a homogeneous distribution of active materials such as sulfur without agglomeration and allows rapid diffusion of ions. In addition, the interlayer made in this study is 30wt% lighter than the existing fiber-type paper layer based on its high porosity and at the same time has a very high 15.5% nitrogen atoms. Excess N atoms including pyridinic-N and pyrrolic-N contained in the interlayer prevent diffusion of LiPSs to the counter electrode through strong chemical bonds with LiPSs, and also greatly improve conductivity, minimizing resistance related to charge transfer. As a result, the cells assembled with them maintain a capacity of 700 mAh g−1 after 500 cycles at 0.5 C. In addition, it can exhibit a capacity of 697 mAh g−1 even at a high current density of 7.0 C.
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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".