Sustainable high yield production of cellulose nanomaterials for easy-cleaning surfaces of cellulose-based materials
Bibliographic record
Abstract
Cellulose nanomaterials with high yield and desired properties were sustainably produced using a facile recyclable acid treatment (oxalic acid) with mineral acid catalysis at ambient pressure. The resultant nanocellulose was uniform in dimensions (diameter and length distributions) and highly dispersible in the aqueous phase. The nanocellulose with yield up to 33.9%, a zeta potential of -53.9 mV, and 100% volume stability (24 h) was achieved via oxalic acid treatment in conjunction with sulfuric acid addition. The coating of such nanocellulose on paper created a uniform and dense layer on the surface, which lowered Gurley air permeability (i.e., prolonging the time required for air flow from 3.9 to 681.9 s per 100 mL). Moreover, the coated paper showed a complete grease barrier after 48 h and presented easy-cleaning behavior. The approach developed in this work offers an adoptable guidance to design green and sustainable easy-cleaning surfaces. In turn, this approach will provide potential applications of nanocellulose for green based packaging and environmental protection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".