Dopamine-Derived Graphite-Like Hard Carbon Materials for High-Performance Li+ Ions Storage
Bibliographic record
Abstract
Graphite anode material is easily powdered under large currents, resulting in a short circuit inside the battery, causing serious safety hazards. Therefore, it is necessary to study a negative electrode material, increase the diffusion channel of lithium ions, increase the layer spacing, reduce the transmission distance, effectively weaken the lithium-ion deposition, and improve the cycle life. A novel organic hard carbon material was prepared by calcining dopamine hydrochloride (DA) at three temperatures. Under the inert atmosphere of 950 °C, the material is fully carbonized, the lattice spacing is 0.367 nm, and it has good lithium-ion transmission activity. After assembling into a battery, after 2000 charge-discharge tests at a high rate of 10C, the charging specific capacity is still 103.3mAh g-1, and the CE remains 101.4%. Dopamine hard carbon anode materials exhibit excellent specific capacity and cycle properties, providing new ideas to support the rapid charging and discharging of hard carbon anode materials.
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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 | 0.001 | 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".