Polyamide/ <scp> SiO <sub>2</sub> </scp> /Gelatin In Situ Composite From <scp>BIC</scp> /Sol–Gel Co‐Reaction for Dual Applications in Hg <sup>2+</sup> Electrochemical Probing and Both Anionic/Cationic Dyes Removal
Bibliographic record
Abstract
ABSTRACT In this study, a novel polyamide (PA)/SiO 2 /gelatin (GL) in situ hybrid material (PA‐Si‐GL) was successfully prepared at room temperature by introducing amphoteric biomass, GL, as a reaction substrate into benzoxazine‐isocyanide chemistry (BIC)/sol–gel reaction system. The systematic characterization of PA‐Si‐GL's chemical structure and fundamental properties was implemented subsequently. The in situ integration of GL with diverse N,O‐containing segments (amide, phenol OH, and SiOSi) present in PA/SiO 2 fraction could strengthen the affinity between PA‐Si‐GL and Hg 2+ /dyes. PA‐Si‐GL's binding for Hg 2+ was reasonably utilized to realize the probing of this highly poisonous heavy metal. With PA‐Si‐GL as the active modifier, the modified glassy carbon electrode (GCE) (termed as PA‐Si‐GL/GCE) exhibited a specific enrichment‐enhanced electrochemical response toward Hg 2+ , with a detection limit as low as 2.8 × 10 −10 mol/L. Concurrently, PA‐Si‐GL can remove both anionic (Congo red [CR]) and cationic (methylene blue [MB]) dyes from contaminant water. The maximum adsorption capacities of PA‐Si‐GL for CR/MB reached 680.1/1001.3 mg/g (298 K), respectively. Mechanistic studies regarding Hg 2+ probing and dyes adsorption by PA‐Si‐GL were carried out by the combination of experimental comparison and chemical calculation.
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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".