Structurally tailored graphene nanosheets as lithium ion battery anodes: an insight to yield exceptionally high lithium storage performance
Why this work is in the frame
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Bibliographic record
Abstract
How to tune graphene nanosheets (GNSs) with various morphologies has been a significant challenge for lithium ion batteries (LIBs). In this study, three types of GNSs with varying size, edge sites, defects and layer numbers have been successfully achieved. It was demonstrated that controlling GNS morphology and microstructure has important effects on its cyclic performance and rate capability in LIBs. Diminished GNS layer number, decreased size, increased edge sites and increased defects in the GNS anode can be highly beneficial to lithium storage and result in increased electrochemical performance. Interestingly, GNSs treated with a hydrothermal approach delivered a high reversible discharge capacity of 1348 mA h g(-1). This study demonstrates that the controlled design of high performance GNS anodes is an important concept in LIB applications.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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