Spectroscopic and Modeling Investigation of Sorption of Pb(II) to ZSM-5 Zeolites
Bibliographic record
Abstract
Abstract Methyl tert-butyl ether (MTBE) was used as a replacement for Pb in gasoline before it was found to be harmful, and for this reason, these two contaminants often coexist in groundwater at older fueling facilities. ZSM-5 is a well-characterized synthetic zeolite that shows promise in the removal of organic contaminants from water. While numerous studies have quantified the adsorption of metal to hydrophilic zeolites, few have investigated the mechanisms for adsorption to hydrophobic zeolites such as ZSM-5. In this study, batch adsorption tests and synchrotron-based extended X-ray absorption fine structure (EXAFS) analyses were conducted to investigate the adsorption of Pb to ZSM-5 in the presence and absence of MTBE. Batch adsorption studies showed that MTBE did not significantly impact Pb adsorption. EXAFS analyses revealed two Pb binding mechanisms: (1) precipitation as a PbO·(H2O) type surface coating and (2) adsorption of Pb at Si surface sites. The PbO·(H2O) type surface coating is more stable at pH 6 due to the formation of solid-phase hydroxide minerals, while the Pb to Si surface site occupancy is constrained by the availability of silanol sites on the surface. Our study provides an understanding of the mechanisms of precipitation and/or adsorption of Pb to hydrophobic zeolites and new insights into the synthesis and/or modification of zeolites to target the removal of co-contaminants from water and wastewater.
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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".