Two-Step Graphene Strategy Enabling Long-Cycle Stability of Silicon Anodes
Bibliographic record
Abstract
A two-step graphene-reinforced hierarchical structure to address the poor cycle stability due to significant volume fluctuations in silicon anodes for lithium-ion batteries (LIBs) is introduced in this study. Fine composite granules (1–2 μm), SiNPs@rGO where silicon nanoparticles (SiNPs) were fully encapsulated by reduced graphene oxide (rGO) flakes, were synthesized by a high-power planetary ball milling technique. The compact structure of the SiNPs@rGO granules effectively suppressed the dispersion loss of Si and Li x Si fragments from the granules. To accommodate the large volume fluctuation of Si in lithiation and delithiation cycles, a hierarchical structure using mechanically flexible and stretchable holey reduced graphene oxide (HrGO) 2D layers was developed. The hierarchical structure of HrGO/SiNPs@rGO composite anode successfully accommodated the volume fluctuations of SiNPs@rGO, thereby markedly enhancing long-cycle stability. Systematic analyses of the characteristic electrochemical properties and morphological evolution of these 2D material-based anodes are reported.
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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) | 0.000 | 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 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".