Two‐Dimensional NiO@C‐N Nanosheets Composite as a Superior Low‐Temperature Anode Material for Advanced Lithium‐/Sodium‐Ion Batteries
Bibliographic record
Abstract
Abstract Most of the anodes used in lithium‐/sodium‐ion batteries (LIBs/SIBs) have poor low‐temperature (LT) performances, which severely limit their applications under LT environment. Herein, two‐dimensional nickel oxide nanosheet encapsulated in N‐doped carbon coated layer (abbreviated as NiO@C−N NSs) is successfully prepared and investigated for the first time as a LT anode for LIBs/SIBs. As a result, the prepared NiO@C−N NSs electrode delivers a high room temperature (RT) Li‐storage capacity (1036 mA h g−1 at 0.05 A g−1) and excellent LT Li‐storage performance (428 mA h g−1 at 0.05 A g−1 at −40 °C). Furthermore, the prepared NiO@C−N NSs also exhibits a superior RT Na‐storage capacity of 529 mA h g−1 at 0.05 A g−1 and superior LT Na‐storage performance. Through electrochemical impedance spectroscopy analysis, we find that the LT Li‐/Na‐storage performances of NiO@C−N NSs electrodes are mainly dominated by the RSEI of SEI membrane formation at the electrode/electrolyte interface. Moreover, the LT Li‐/Na‐storage properties of NiO@C−N NSs can be effectively improved by using commercial LT electrolyte with low viscosity and low melting point.
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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".