Thermally Reduced Graphene/MXene Film for Enhanced Li‐ion Storage
Bibliographic record
Abstract
Abstract Two‐dimensional transition‐metal carbides called MXenes are emerging electrode materials for energy storage due to their metallic electrical conductivity and low ion diffusion barrier. In this work, we combined Ti2CTx MXene with graphene oxide (GO) followed by a thermal treatment to fabricate flexible rGO/Ti2CTr film, in which electrochemically active rGO and Ti2CTr nanosheets impede the stacking of layers and synergistically interact producing ionically and electronically conducting electrodes. The effect of the thermal treatment on the electrochemical performance of Ti2CTx is evaluated. As anode for Li‐ion storage, the thermally treated Ti2CTr possesses a higher capacity in comparison to as‐prepared Ti2CTx. The freestanding hybrid rGO/Ti2CTr films exhibit excellent reversible capacity (700 mAh g−1 at 0.1 Ag−1), cycling stability and rate performance. Additionally, flexible rGO/Ti3C2Tr films are made using the same method and also present improved capacity. Therefore, this study provides a simple, yet effective, approach to combine rGO with different MXenes, which can enhance their electrochemical properties for Li‐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 | 0.000 | 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) | 0.002 | 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".