Recovery of oxidized two-dimensional MXenes through high frequency nanoscale electromechanical vibration
Bibliographic record
Abstract
Abstract MXenes hold immense potential given their superior electrical properties. The practical adoption of these promising materials is, however, severely constrained by their oxidative susceptibility, leading to significant performance deterioration and lifespan limitations. Attempts to preserve MXenes have been limited, and it has not been possible thus far to reverse the material’s performance. In this work, we show that subjecting oxidized micron or nanometer thickness dry MXene films—even those constructed from nanometer-order solution-dispersed oxidized flakes—to just one minute of 10 MHz nanoscale electromechanical vibration leads to considerable removal of its surface oxide layer, whilst preserving its structure and characteristics. Importantly, electrochemical performance is recovered close to that of their original state: the pseudocapacitance, which decreased by almost 50% due to its oxidation, reverses to approximately 98% of its original value, with good capacitance retention ( ≈ 93%) following 10,000 charge–discharge cycles at 10 A g−1. These promising results allude to the exciting possibility for rejuvenating the material for reuse, therefore offering a more economical and sustainable route that improves its potential for practical translation.
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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) | 0.001 | 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".