Effect of the coexistence of SO32− and PO43− on the adsorption performance of zeolite-loaded FeOOH@ZnO for S2−
Bibliographic record
Abstract
Abstract The present study deals with the synthesis of zeolite-loaded FeOOH@ZnO by hydrothermal method and investigates the effects of coexisting SO32− and PO43− ions in the aqueous solution on the adsorption performance for S2−. The results showed that the HNO3-modified zeolite loaded with FeOOH@ZnO (FeOOH@ZnO/HZ) resulted in a maximum S2− removal rate of ≈98%. The adsorbent's performance on removing S2− was significantly enhanced, compared with NaOH and ZnCl2-modified zeolites loaded with FeOOH@ZnO, and the adsorption was proved to be a heat-absorbing process. When SO32− and PO43− coexisted with S2−, SO32− and PO43− had a significant influence on the adsorption properties of FeOOH@ZnO/HZ. When three ions of S2−, SO32− and PO43− were present simultaneously, the adsorption performance of FeOOH@ZnO/HZ on S2− was further, and the removal rate dropped to about 80%. Moreover, FeOOH@ZnO/HZ also adsorbed PO43− and SO32− in the system containing multiple ions, but the adsorption rates of PO43− and SO32− were much lower than S2−. This indicated that the adsorption of S2− in the presence of FeOOH@ZnO/HZ dominates under competitive conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".