Electrospun Cellulose-Acetate/Chitosan Fibers for Humic-Acid Removal: Improved Efficiency and Robustness with a Core-Sheath Design
Bibliographic record
Abstract
Recycling biomass waste into functional materials has attracted much attention, and a rational structural design can make more effective use of each component. In our previous work, the fabrication of electrospun cellulose-acetate (CA)/chitosan (CS) adsorbents for humic-acid (HA) removal guided by the intermolecular interaction mechanism was demonstrated. Herein, a core-sheath structure was designed via one-step co-axial electrospinning, where a mixture of CS and CA was employed as the sheath layer to efficiently adsorb HA, and cellulose nanocrystals (CNCs) derived from waste cotton fabrics were incorporated into the CA core as load-bearing components. Compared to the non-layered electrospun CS/CA fibers, all the CS/CA-CNC fibers with a core-sheath structure exhibited smaller diameters, greater homogeneity, and significantly improved mechanical strength. Meanwhile, their maximum adsorption capacities towards HA had no significant differences. Even after the complete hydrolysis of CA into cellulose, the electrospun fibers maintained the fibrous structures and showed a higher tensile strength while exhibiting an acceptable adsorption capacity towards HA. Therefore, this work demonstrates the importance of rational design in the efficient preparation of functional materials and the feasibility of using electrospun core-sheath fibers derived from biomass wastes for the removal of water contaminants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".