Recent progress in cellulose-based electrospun nanofibers as multifunctional materials
Bibliographic record
Abstract
Cellulose, the most abundant natural polymer, has good biocompatibility, biodegradability, and non-toxicity, which make it and its derivatives promising candidates for the fabrication of multifunctional materials, while maintaining sustainability and environmental friendliness. The combination of electrospinning technology and cellulose (and its derivatives) provides a feasible approach to produce nanostructured porous materials with promising functionalities, flexibility, renewability and biodegradability. At the same time, it enables value-added applications of cellulose and its derivatives that are derived from nature or even biomass waste. This review summarizes and discusses the latest progress in cellulose-based electrospun nanofibers, including their construction methods and conditions, various available raw materials, and applications in multiple areas (water treatment, biomaterials, sensors, electro-conductive materials, active packaging, and so on), which are followed by the conclusion and prospects associated with future opportunities and challenges in this active research area.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".