Synthesis and characterization of polyacrylamide and <scp> <i>Moringa oleifera</i> </scp> seed powder‐based hydrogels
Bibliographic record
Abstract
Abstract In the present study, crosslinked poly(acrylamide) (PAM)‐based hydrogels were synthesized utilizing different ratios of N,N′ ‐methylenebisacrylamide (0.0026, 0.0078, 0.1297 mol), while incorporating unmodified Moringa oleifera (MO) seed powder at different proportions (2.5%, 5%, and 10% w/w). The primary objective of the study was to rigorously evaluate the steady‐state dynamic swelling, its behaviour at different pH values, surface morphology, and thermal stability, to position the material as a sustainable and low‐cost biosorbent. Through FT‐IR spectroscopy, the formation of the compound hydrogels was confirmed through the interactions between the functional groups of the MO seed powder with the polymer chains. Likewise, the SEM micrographs showed that the incorporation of the natural macromolecule increased the porosity. The best results were obtained in a homogeneous and interconnected structure for the hydrogel with 5% of MO seed powder. In the dynamic swelling tests, the highest water absorption was observed at basic pH, reaching 3050%. Furthermore, the swelling kinetics were best described by the mixed kinetic (MK) model (R 2 > 0.990), confirming the process was governed by a hybrid mechanism of solvent diffusion and structural polymer relaxation; Thermogravimetric analysis revealed that the incorporation of MO improves thermal stability; the hydrogels showed relevant advantages by integrating the MO without chemical modification, using a practical and ecological approach. The results obtained position this type of hydrogel as a sustainable alternative with potential application in water treatment and environmental technology.
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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".