Tailoring Hydronium ion Driven Dissociation-Chemical Cross-Linking for Superfast One-Pot Cellulose Dissolution and Derivatization to Build Robust Cellulose Films
Bibliographic record
Abstract
Concepts of sustainability must be developed to overcome the increasing environmental hazards caused by fossil resources. Cellulose derivatives with excellent properties are promising biobased alternatives for petroleum-derived materials. However, a one-pot route to achieve cellulose dissolution and derivatization is very challenging, requiring harsh conditions, high energy consumption, and complex solubilizing. Herein, we design a one-pot tailoring hydronium ion driven dissociation-chemical cross-linking strategy to achieve superfast cellulose dissolution and derivatization for orderly robust cellulose films. In this strategy, there is a powerful driving force from organic acid with a p K a below 3.75 to dissociate H + and trigger the dissolution and derivatization of cellulose under the addition of H 2 SO 4 . Nevertheless, the driving force can only trigger a partial swelling of cellulose but without dissolution when the p K a of organic acid is above 4.26 for the dissociation of H + is inhibited by the addition of inorganic acid. The cellulose film has high transmittance (up to ∼90%), excellent tensile strength (∼122 MPa), and is superior to commercial PE film. Moreover, the tensile strength is increased by 400% compared to cellulose film prepared by the ZnCl 2 solvent. This work provides an efficient solvent, which is of great significance for emerging cellulose materials from renewable materials.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".