PEDOT:PSS‐Facilitated Directionally 3‐D Assembled MXene‐Based Aerogel for High‐Performance Chemoresistive Sensing & Breath Analysis
Bibliographic record
Abstract
MXene has garnered growing interest in the field of electrochemistry, thanks to its unique electrical and surface characteristics. Nonetheless, significant challenges persist in realizing its full potential in chemoresistive sensing applications. In this study, a novel unidirectional freeze-casting approach for fabricating a Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)-facilitated vertically aligned MXene-based aerogel with enhanced chemoresistive sensing properties was introduced. Firstly, the persistent challenge of poor gelation in MXene was addressed by formulating a nanohybrid of MXene and PEDOT:PSS, which acted as flexible conductive nanobinder. Employing a unique freeze-casting method, MXene flakes interconnected by PEDOT:PSS, were stabilized into a flexible, vertically aligned structure, leading to maximum surface exposure and enhanced robustness. The resulting 3-dimentional (3-D) aerogel exhibited a fast, heightened chemoresistive response of 7 to 50 parts per million (ppm) acetone and expanded the working range to between 10 parts per billion (ppb)-8000 ppm. Interfacial heterostructures formed between MXene and PEDOT:PSS, provided active sites, reduced activation energy, and enhanced selectivity. Modulated MXene bandgap, and its electron mobility further facilitated electron transfer, and enhanced signal strength. The sensor showed excellent biocompatibility and was also successfully employed as a breathalyzing tool, for on-demand alcohol consumption monitoring.
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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".