2D Ultrathin NiCo<sub>2</sub>S<sub>4</sub> Nanosheets-Assisted 3D Highly Stable Lithium Metal Anode
Bibliographic record
Abstract
Lithium (Li) metal is usually considered one of the most promising anode candidates for next-generation batteries owing to its extremely high specific capacity and low reduction potential. However, the application of Li metal anode is still hindered by the uncontrolled growth of dendritic Li and extreme volume fluctuation during cycles. Herein, we demonstrate a flexible and self-supporting 3D interlaced carbon nanofibers coated with 2D ultrathin NiCo2S4 nanosheets (denoted as CNF@NiCo2S4) which are containing high lithiophilicity and porous structure. This unique structure can significantly reduce the exchange current density and improve the performance for plating Li. Moreover, metallic Li can be further confined within the interspace among the CNF and inside the porous carbon nanoboxes significantly avoiding dendritic Li formation. The CNF@NiCo2S4 composite anode exhibits a long-running lifespan for 1000h with an exceptionally low voltage hysteresis. Full cells with LiFePO4 cathode and LiǀCNF@NiCo2S4 anode show typical voltage profiles but enhanced cycle performance than that of LiFePO4 coupling with bare Li anode at low N/P ratio.
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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".