Investigation of the Metal Cations Adsorption Selectivity UsingNanocavities-Rich Polyamine-Cross-Linked PMVEAMA
Bibliographic record
Abstract
Water contamination with toxic metal ions is one of the major problems of environmental pollution, caused by intensified economic development.Therefore, efficient sorptive systems capable of binding metal cations are of great interest.Herein, we present the synthesis of materials containing nanocavities created by the cross-linking of poly(methyl vinyl ether-alt-maleic anhydride) with four structurally different polyamines: tris(2-aminoethyl)amine (TREN), piperazine, triethylenetetramine (TETA), and 4,7,10-trioxa-1,13-tridecanediamine (TRI-OXA).The easiness of the synthetic protocol and the biocompatibility of bare polymer indicate the convenience of the proposed adsorbents.The materials were subjected to adsorption of Al(III), Mn(II), Hg(II), and Cd(II) ions from their binary, ternary, and quaternary systems.The ions' adsorption percentages were established using XRF analysis, indicating the dependence of the materials' adsorption ability on the cross-linking agent used.Such findings are strictly related to the size of the polyamine used, determining the distances between subsequent polymer chains, and thus the size of internal nanocavities formed.
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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) | 0.000 | 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".