Kinetic and Thermodynamic Investigations of Zn(II) Adsorption on Microcrystalline Anthracene Modified with 8‐Hydroxyquinoline and Its Application to the Preconcentration and Determination of Trace Zinc
Bibliographic record
Abstract
Abstract A new method that utilizes microcrystalline anthracene modified with 8‐hydroxyquinoline as an adsorbent has been developed for the preconcentration of trace Zinc(II). The possible reaction mechanism is discussed in detail. The influences of different parameters, such as acidity, other metal ions, the amounts of 8‐hydroxyquinoline and anthracene, etc. on the enrichment yield of Zn(II) have been studied to optimize the experimental conditions. The experimental data were fitted well with the pseudo‐second‐order kinetic model and Langmuir model at all studied temperatures and the maximum adsorption capacity was 32.58 mg·g−1 (300 K). The thermodynamic parameters (ΔGθ, ΔHθ and ΔSθ) showed the feasibility, exothermic and spontaneous nature of the adsorption at 280∼320 K. Experiments indicate that Zn(II) can be completely separated from Cu(II), Co(II), Cd(II), Mn(II), Ni(II) in the eluent. The recovery of this method is in the range of 96.0%∼105.0% with preconcentration factor of 100 and the limit of detection after preconcentration is 0.068 μg·L−1. The proposed method has been successfully applied to the determination of trace Zn(II) in effluents and synthetic water sample having a composition similar to certified water sample SLRS‐4 (NRC, Canada). Analytical results obtained by this recommended method were very satisfactory.
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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".