Enhanced removal of per- and poly-fluoroalkyl substances (PFAS) by modified clay: Adsorption behavior, simulation, and regeneration
Bibliographic record
Abstract
A modified clay adsorbent was developed by coating poly(diallyldimethylammonium) chloride (PDADMAC) to improve its performance in removing per- and poly-fluoroalkyl substances (PFAS) from water. The adsorption equilibrium was well described by the Freundlich isotherm, with K f values of 2.29 ± 0.80 (mg/g)(L/mg)¹⁄ⁿ for perfluorobutanoic acid (PFBA) and 38.21 ± 6.73 (mg/g)(L/mg)¹⁄ⁿ for perfluorooctanoic acid (PFOA), while the kinetic behavior fit both pseudo-first-order and pseudo-second-order models, with all R² values exceeding 0.95. Adsorption performance decreased with increasing pH, particularly for short-chain PFAS. Compared to NaCl, the presence of natural organic matter had a more pronounced inhibitory effect on PFAS uptake. The PDADMAC-modified clay demonstrated excellent reusability, retaining >98% of its initial efficiency after five regeneration cycles using simple NaCl brine. This effective brine-based regeneration outperformed commercial adsorbents such as ion exchange resins and activated carbon. Quantum mechanical calculations and molecular dynamics simulations revealed that adsorption is mainly driven by noncovalent interactions, with strong electrostatic attraction (–42.73 kcal/mol for PFBA and –43.26 kcal/mol for PFOA) complemented by van der Waals forces (–10.03 kcal/mol for PFBA and –15.80 kcal/mol for PFOA). These negative interaction energies confirm the thermodynamic favourability of adsorption. These results demonstrate that PDADMAC modification substantially improves performance of clay-based adsorbents and offers a practical, low-cost, and scalable strategy for PFAS remediation in water treatment applications. • A polymer-modified clay adsorbent was developed for PFAS removal from water. • PFAS uptake was influenced by pH and natural organic matter. • Effective regeneration was achieved using 1% NaCl solution. • QM analysis revealed noncovalent interactions as key adsorption mechanism. • Molecular simulation aligned well with experimental adsorption behavior.
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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".