Magnetic phosphorylated lignocellulosic fibers: A hybrid material for water purification – Part I material synthesis
Bibliographic record
Abstract
Magnetic functionalized phosphorylated papers were synthesized using a simple and efficient method. Several characterizations were carried out to determine the structure, morphology and types of interaction between the phosphorylated cellulose fibers (PKF) and the magnetic particles. The results show excellent swelling of the cellulose structure, without altering its morphology, indicating the robustness of the method and the preservation of the fundamental properties of the fibers. X-ray diffraction confirmed the incorporation of Fe₃O₄ into the cellulose matrix, as shown by characteristic reflections of magnetite and cellulose. The broadening of Bragg peaks indicated the formation of spinel-structured Fe₃O₄ particles remaining strongly attached to fibers even after extensive washing because of strong cellulose-magnetite interactions. The synthesis approach preserved the structural integrity of the fibers while enhancing their specific surface area and accessibility. Surface energy analysis revealed a high adhesion energy between PKF and Fe₃O₄, preventing particle agglomeration and ensuring homogeneous distribution. The presence of Fe₃O₄ led to an overall improvement in mechanical properties due to its uniform dispersion within the fibrous matrix. Thermogravimetric analysis (TGA) showed the high thermal resistance of both PKF and PKF-Fe₃O₄ composite. To assess the long-term stability of the magnetic phosphorylated paper, iron leaching tests were performed at different pH levels. The composite showed minimal Fe release, with iron concentrations remaining below 0.2 mg/L for pH values above 3, indicating low environmental risk. These results confirm that PKF-Fe₃O₄ composite is a robust, stable, and thermally resistant material, making it a promising candidate for advanced applications requiring magnetic cellulose-based composites. • Phosphorylated kraft fibers were modified with magnetite to create hybrid composites. • The material exhibits flame retardancy and enhanced mechanical strength. • Minimal iron leaching ensures structural stability in various conditions. • Robust synthesis preserves cellulose morphology and enhances composite performance. • High affinity between fibers and magnetite promotes efficient composite formation.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".