Application of Iron Nanoparticles Synthesized by Green Tea for the Removal of Hexavalent Chromium in Column Tests
Bibliographic record
Abstract
Nano zero valent iron particles (nZVI) are popular the last few years because of the numerous applications in remediation of a wide range of pollutants in contaminated soils and aquifers.The nZVI particles can be 10 -1000 times more reactive than granular or micro-scale ZVI particles due to the small particle size, large specific surface area and high reactivity.An alternative green synthesis procedure was used for the production of nano zero valent iron particles (nZVI) using green tea (GT) extract, which is characterized by its high antioxidant content.Polyphenols in green tea extract possess double role in the synthesis of nZVI, because they not only reduce ferric cations, but also protect nZVI from oxidation and agglomeration as capping agents.The objective of current study was to simulate ata laboratory scale the attachment of GT-nZVI particles on soil material and study the effectiveness of attached nanoparticles for removing hexavalent chromium (Cr(VI)) from contaminated groundwater flowing through the porous soil bed.Column tests were carried out with various flowrates in order to examine the effect of contact time between the attached on porous medium nZVI and the flow-through solution on Cr(VI) reduction.After the completion of column tests the soil material in each column was split in 5 vertical sections, which were further subjected to chemical analyses and leaching tests.According to the results of the study increasing the contact time favors the reduction and removal of Cr(VI) from the aqueous phase.The reductive precipitation of Cr can be described as a reaction that follows a pseudo-first order kinetic law, with rate constant equal to k = 0.0243 ± 0.0011 min -1 .Leaching tests indicated that precipitated chromium is not soluble.In the examined soil material, the total amount of precipitated Cr was found to range between 280 and 890 mg/(kg soil), while soluble Cr was less than 1.4 mg/kg and most probably it was due to the presence of residual Cr(VI) solution in the porosity of soil.
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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 | 0.001 |
| 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".