High Capacity and High Efficiency Maple Tree-Biomass-Derived Hard Carbon as an Anode Material for Sodium-Ion Batteries
Bibliographic record
Abstract
Sodium-ion batteries (SIBs) are in the spotlight because of their potential use in large-scale energy storage devices due to the abundance and low cost of sodium-based materials. There are many SIB cathode materials under investigation but only a few candidate materials such as carbon, oxides and alloys were proposed as anodes. Among these anode materials, hard carbon shows promising performances with low operating potential and relatively high specific capacity. Unfortunately, its low initial coulombic efficiency and high cost limit its commercial applications. In this study, low-cost maple tree-biomass-derived hard carbon is tested as the anode for sodium-ion batteries. The capacity of hard carbon prepared at 1400 °C (HC-1400) reaches 337 mAh/g at 0.1 C. The initial coulombic efficiency is up to 88.03% in Sodium trifluoromethanesulfonimide (NaTFSI)/Ethylene carbonate (EC): Diethyl carbonate (DEC) electrolyte. The capacity was maintained at 92.3% after 100 cycles at 0.5 C rates. The in situ X-ray diffraction (XRD) analysis showed that no peak shift occurred during charge/discharge, supporting a finding of no sodium ion intercalates in the nano-graphite layer. Its low cost, high capacity and high coulombic efficiency indicate that hard carbon is a promising anode material for sodium-ion batteries.
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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 | 0.001 |
| 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".