Self‐supporting, low‐tortuosity hard carbon for superior sodium‐ion batteries
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Hard carbon stands out as the most promising candidate for anodes in sodium‐ion battery. Nevertheless, addressing the challenges of low initial Coulombic efficiency and rate performance is crucial for practical applications. In this study, we employed a dimensionally designed approach, using six different biomass precursors, to preserve their inherent fine hierarchical morphological structures and appearances during the synthesis of self‐supporting carbon materials. Benefiting from its low‐tortuosity structure that facilitates electron and ion transport, as well as its surface‐enriched C=O functional groups and significant closed micropore areas, the obtained carbon material exhibits excellent electrochemical performance in sodium‐ion storage, demonstrated by finite element simulation. Notably, the carbonized basswood exhibited a remarkable initial Coulombic efficiency of up to 92.4% and demonstrated outstanding rate performance, achieving a capacity of 223.3 mAh·g −1 at a high current density of 2 A·g −1 . In addition, thorough investigation was conducted on the influence of microstructure on the sodium storage behavior of hard carbon. Ex situ X‐ray diffraction (XRD) was used to confirm that the capacity in the plateau region originates from interlayer insertion and closed‐pore filling, which is consistent with the results obtained from small‐angle X‐ray scattering. These findings underscore the immense potential of leveraging surface functionalization and structural design to bolster the performance of hard carbon, paving the way for promising future advancements in this field.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it