Xylan derived carbon dots composite with cotton cellulose paper as fluorescence sensor for real time detection Cu2+
Bibliographic record
Abstract
Abstract Cotton cellulose paper composited with fluorescence carbon dots (CDs) has shown potential for Cu2+ detection in environmental monitoring. In this study, a solid-state detection platform was developed using biomass-based fluorescent sensors (CPU-CDs) composed of xylan-derived CDs (U-CDs) and cotton cellulose paper. The fluorescence platform was nanoengineered to monitor Cu2+ changes via spectral and colorimetric dual-modal methods. CPU-CDs exhibits reusability, non-toxicity, excellent fluorescence characteristics and biocompatibility. Besides, CPU-CDs has a complex network structure and a large number of hydroxyl and amino groups, which can realize a high loading rate of U-CDs and provide more binding sites for the detection and response of Cu2+. CPU-CDs displays high effectiveness and sensitivity for Cu2+. Additionally, the detection limit of CPU-CDs for Cu2+ as low as 0.14 μM that was well below U.S. EPA safety levels (20 μM). Practical application indicated that CPU-CDs could achieve precision response of Cu2+ change in water environment with recovery range of 90%-119%. This strategy demonstrated a promising biomass solid-state fluorescence sensor for Cu2+ detection for water treatment research.
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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".