2D/0D Heterojunction Fluorescent Probe with Schottky Barrier Based on Ti<sub>3</sub>C<sub>2</sub>T<sub>X</sub> MXene Loaded Graphene Quantum Dots for Detection of H<sub>2</sub>S During Food Spoilage
Bibliographic record
Abstract
Abstract Hydrogen sulfide (H 2 S) contamination of food has raised widespread public health concerns, leading to substantial medical and economic burdens. Herein, a 2D/0D heterojunction fluorescent probe (TCTG) with Schottky barriers (SB) is designed and synthesized, utilizing Ti 3 C 2 T x MXene‐loaded graphene quantum dots (GQDs), for the detection of H 2 S during food spoilage. The microstructures observed through SEM and TEM reveal that uniformly sized GQDs are evenly attached to the surface of a monolayer Ti 3 C 2 T x . The chemisorption between GQDs and Ti 3 C 2 T x facilitates charge transfer and the formation of SB, resulting in intramolecular charge transfer (ICT) effects. With the introduction of H 2 S, TCTG (50%) exhibits the highest sensitivity, selectivity, and anti‐interference properties, with ultra‐fast fluorescence transient reaction (3s) and remarkably low detection limit of 41.82 ppb as well as noticeable color change. When TCTG (50%) reacted with H 2 S, the ICT effects are inhibited, leading to the recovery of photoinduced electron transfer (PET) and fluorescence quenching. Notably, probe TCTG is effectively utilized to detect changes in H 2 S levels in raw foods to assess their quality. Overall, the significance of this study is its potential to revolutionize food spoilage detection, offering a fast, reliable, and sensitive method to ensure food safety and reduce associated health and economic burdens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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; both teacher heads agree on what is shown here.
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".