Ti <sub>3</sub> C <sub>2</sub> /Ni/Sm‐Based Screen‐Printed‐Electrode for the ECL Detection of Hydrogen Peroxide as a Milk Preservative
Bibliographic record
Abstract
Abstract Hydrogen peroxide is a widely used agent in the food industry for its sterilization, packaging, and transportation capabilities. However, its excessive concentration can lead to adverse health effects, especially in gastrointestinal conditions. As a result, it is crucial to detect its presence in food products, particularly milk. To address this need, we have developed a state‐of‐the‐art MXene‐based ECL system that can detect low‐concentration hydrogen peroxide levels with high sensitivity and accuracy. Our system incorporates 2D MXene structures, which not only enhance electrode conductivity but also form a complex with Ni/Sm‐LDH (layered double hydroxide) that enables detection across a broad linear range of 0.05–2 ppm in real samples. Furthermore, we have successfully lowered the detection limit to an impressive 0.005 ppm. With this innovative approach, we can ensure the safety and quality of food products, making it a significant breakthrough in the food industry.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".