Preconcentration by Coprecipitation of Copper and Nickel with Mo(VI)/Triazole Derivative System and Their Determinations by Flame Atomic Absorption Spectrometry in Food and Water Samples
Bibliographic record
Abstract
Abstract A new separation and preconcentration technique based on coprecipitation of Cu(II) and Ni(II) ions by the aid of Mo(VI)/di‐ tert ‐butyl{methylenebis[5‐(chlorobenzyl)‐4 H ‐1,2,4‐triazol‐3,4‐diyl]}biscarbamate (BUMECTAC) precipitate has been established. The Mo(VI)/BUMECTAC precipitate was dissolved by concentrated HNO 3 and the solution was completed to 5.0 mL with distilled/deionized water. The levels of the analyte ions were determined by flame atomic absorption spectrometer. The effects of experimental conditions like HNO 3 concentration, amount of BUMECTAC and Mo(VI), sample volume, etc. and also the influences of some foreign ions were investigated in detail on the quantitative recoveries of analyte ions. The preconcentration factors were found to be 40 for Cu(II) and 100 for Ni(II) ions. The detection limits for Cu(II) and Ni(II) ions based on 3 σ ( N :10) were 0.43 and 0.70 µg L −1 , respectively. The relative standard deviations were found to be lower than 4.0% for both analyte ions. The accuracy of the method was checked by spiked/recovery tests and the analysis of two certified reference materials (Environment Canada TM‐25.3 and CRM‐SA‐C Sandy Soil C). The procedure was successfully applied to sea water and stream water as liquid samples and baby food as solid sample in order to determine the levels of Cu(II) and Ni(II) ions.
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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".