An In Situ Procedure for the Preparation of Zeolitic Imidazolate Framework‐8 Polyacrylamide Hydrogel for Adsorption of Aqueous Pollutants
Bibliographic record
Abstract
Abstract Metal–organic frameworks (MOFs) have attracted a lot of attention in recent years because of their high surface area and tunable porosities, which allow them to serve as excellent and versatile adsorbents for pollutants in water/wastewater. One of the demanding challenges of using MOFs is that they need to be supported on a substrate or in a matrix to be easier to operate and more efficiently used. This work presents a simple in situ method of synthesizing one of the most popular MOF particles, zeolitic imidazolate framework 8 (ZIF‐8), in a polyacrylamide (PAM) hydrogel using a zinc hydroxide PAM composite as a precursor gel. Characterization of the prepared ZIF‐8 PAM composite hydrogel by scanning electron microscope, energy‐dispersive X‐ray spectroscopy, X‐ray powder diffraction, Fourier‐transform infrared spectroscopy, and X‐ray photoelectron spectroscopy confirms the successful synthesis of ZIF‐8 particles on the surface of and inside the PAM hydrogel. To test the potential of this novel material as an adsorbent, its ability to remove humic acid (HA), a model organic pollutant, from water is evaluated. The maximum adsorption capacity for HA is found to be 111.5 ± 3.0 mg g−1 ZIF‐8, comparable to the performance of other adsorbents for the removal of HA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".