Efficient preparation of nanoscale zero‐valent iron by high gravity technology for enhanced Cr(VI) removal
Bibliographic record
Abstract
Abstract Owing to its strong reducibility capacity, nanoscale zero‐valent iron (nZVI) can be widely used in the treatment of wastewater. In this study, nZVI particles with an average size of 14 nm were continuously prepared using a rotating packed bed (RPB) reactor with stainless wire mesh packing. The effects of the surfactant type and the rotating speed of the RPB reactor on the particle size of nZVI were investigated. The results indicated that the average particle size could be notably reduced with the proper addition of PVP in the preparation process. Meanwhile, the particle size could be further decreased by increasing the rotating speed of the RPB. Compared to a stirred tank reactor (STR), the RPB reactor had nZVI with a smaller particle size and a much shorter reaction time. The as‐prepared nZVI was further employed to remove Cr(VI) in the simulated sewage. The results indicated that lower pH, higher nZVI dosage, and higher temperature were beneficial to the efficient removal of Cr(VI). The removal process of Cr(VI) well conformed to a pseudo‐first‐order kinetic model. Thermodynamic studies showed that the reduction of Cr(VI) by nZVI was a spontaneous endothermic reaction process with increased entropy. In addition, nZVI prepared in the RPB displayed higher removal efficiency than the counterpart in the STR, and the removal rate was greatly increased by 17.4 times.
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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".