Gas Pickering Emulsion Templated Hollow Carbon for High Rate Performance Lithium Sulfur Batteries
Bibliographic record
Abstract
A CO2 in water nanoparticle stabilized Pickering emulsion is used to template micrometer sized hollow porous nitrogen doped carbon particles for high rate performance lithium sulfur battery. For the first time, nanoparticles serve the dual role of an emulsion stabilizer and a pore template for the shell, directly utilizing in situ generated CO2 bubbles as template for the core. The minimalistic nature of this method does not require expensive surfactants or additional core templates. Upon polymerization of melamine formaldehyde onto CO2, a robust polymer/silica composite shell is formed and transformed into a porous shell upon washing. The micrometer‐sized hollow morphology in combination with its nitrogen rich porous shell demonstrates impressive rate capabilities of 670 and 500 mAh g−1 even at a high rate of 7C and 9C, respectively. This material also possesses excellent cycle durability, exhibiting a low capacity decay of 0.088%/cycle over 300 cycles. Measurement of the shuttle current and impedance provides interesting insight into the polysulfide mass transfer mechanism of hollow structured sulfur hosts.
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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) | 0.001 | 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".