Mechanistic Study of Selective Adsorption of As(V) by a Surface Ion-Imprinted Diatomite-Based Adsorbent
Bibliographic record
Abstract
In this study, a novel As(V) ion-imprinted and 4-picolinic acid (4-PA)-grafted porous diatomite (DE)-based adsorbent (As(V)-IID) was prepared by using the surface ion imprinting technique. The results of the selective adsorption experiment show that the adsorption capacity of As(V) on As(V)-IID reaches 62.78 mg/g in a solution with an initial As(V) concentration of 25 mg/L and a pH value that is near pH 4.0 of the imprinting. The selectivity coefficients ( K ) of As(V) with respect to Cr(VI) and Mo(VI) were up to 12.14 and 27.79, respectively. The binding process was described well by the pseudo-second-order kinetics and Weber–Morris and Langmuir models. Fourier transform infrared spectra (FTIR), scanning electron microscopy energy dispersive X-ray spectroscopy (SEM-EDS), and X-ray photoelectron spectroscopy (XPS) analyses suggested that the nitrogen of secondary amide and pyridine was the main imprinting site and played a crucial role in the selectivity of binding of As(V) to As(V)-IID. To further validate the sorption mechanisms, density functional theory (DFT) was employed to study the properties of binding of As(V), Cr(VI), and Mo(VI) with As(V)-IID. The computational results showed that the As(V) was selectively recognized by complexing with N-containing functional groups of the As(V)-IID surface into a tridentate mononuclear configuration with a minimal binding energy ( E b ) of −18.16 eV, which was completely consistent with characterization analyses. This work revealed the selective adsorption mechanisms of As(V)-IID for As(V) and provided new insight into the selective recognition of oxyanions from water by ion-imprinted adsorbents.
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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 | 0.001 | 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".