Meta-analyses of the evolution of MXene synthesis for bioengineering and artificial intelligence-driven applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The year 2011 marked a breakthrough in material science innovation with the discovery of MXenes, an emerging family of two-dimensional transition metal-based nanomaterials. Owing to their distinctive properties, MXenes have rapidly surfaced as transformative materials, particularly in energy-storage and nanomedicine. In this review, we systematically explore the evolution of MXene synthesis, from its discovery to current advancements, focussing on their bioengineering applications, through a meta-analytic and bibliometric lens. We discuss synthesis methods, ranging from hydrofluoric acid (HF)-based etching to non-HF approaches, along with post-synthesis processes like intercalation, delamination and surface functionalization, that tailor MXene properties for biomedical therapeutics. We also overview key microscopy, spectroscopy and diffraction-based characterization methods, to understand their structure and functionality. Additionally, discussion on artificial intelligence (AI)-driven innovations highlights the significant shift in material science. By connecting synthesis methods with resulting characteristics and meta-analyses trends, this review emphasizes MXenes' transformative potential in regenerative therapeutics and diagnostics.
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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 | 0.001 | 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 | 0.001 | 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