Electrochemical Sensor Based on Spent Coffee Grounds Hydrochar and Metal Nanoparticles for Simultaneous Detection of Emerging Contaminants in Natural Water
Bibliographic record
Abstract
This research describes the modification of a glassy carbon electrode with spent coffee grounds hydrochar (HDC) and copper nanoparticles (CuNPs) for the simultaneous determination of hydroxychloroquine sulfate (HCS) and bisphenol A (BPA). Scanning electron microscopy, EDS and cyclic voltammetry were used to characterize the nanocomposite. The analytical parameters were optimized and the sensing platform was applied for the determination of HCS and BPA using square-wave voltammetry (SWV). For HCS, the linear range was from 1.0 μmol L−1 to 50 μmol L−1, with an LOD and LOQ of 0.46 and 1.53 μmol L−1, respectively. For BPA, the linear range was from 0.5 μmol L−1 to 10 μmol L−1, with an LOD and LOQ of 0.31 μmol L−1 and 1.06 μmol L−1, respectively. Finally, the developed electrochemical sensor was applied for the quantification of the emerging contaminants in natural water, with recoveries between 94.8% and 106.8% for HCS and 99.6% and 105.2% for BPA. Therefore, HDC-CuNPs demonstrated themselves to be a good alternative as a sustainable and cheaper material for application in electroanalyses.
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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 | 0.000 | 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 teacher head, 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".