Three Birds with One Fe<sub>3</sub>O<sub>4</sub> Nanoparticle: Integration of Microwave Digestion, Solid Phase Extraction, and Magnetic Separation for Sensitive Determination of Arsenic and Antimony in Fish
Bibliographic record
Abstract
An environmentally friendly and fast sample treatment approach that integrates accelerated microwave digestion (MWD), solid phase extraction, and magnetic separation into a single step was developed for the determination of arsenic and antimony in fish samples by using Fe3O4 magnetic nanoparticles (MNPs). Compared to conventional microwave digestion, the consumption of HNO3 was reduced significantly to 12.5%, and the digestion time and temperature were substantially decreased to 6 min and 80 °C, respectively. This is largely attributed to Fe3O4 magnetic nanoparticles being a highly effective catalyst for rapid generation of oxidative radicals from H2O2, as well as an excellent absorber of microwave irradiation. Moreover, potential interferences from sample matrices were eliminated because the As and Sb species adsorbed on the nanoparticles were efficiently separated from the digests with a hand-held magnet prior to analysis. Limits of detection for arsenic and antimony were in the range of 0.01-0.06 μg g(-1) and 0.03-0.08 μg g(-1) by using hydride generation atomic fluorescence spectrometry, respectively, and further improved to 0.002-0.005 μg g(-1) and 0.005-0.01 μg g(-1) when inductively coupled plasma mass spectrometry was used as a detector. The precision of replicate measurements (n = 9) was better than 6% by analyzing 0.1 g test sample spiked with 1 μg g(-1) arsenic and antimony. The proposed method was validated by analysis of two certified reference materials (DORM-3 and DORM-4) with good recoveries (90%-106%).
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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".