Utilization of discarded crop straw to produce cellulose nanofibrils and their assemblies
Bibliographic record
Abstract
A tremendous amount of wheat straw (WS) has been generated by wheat crops every year, while only a small percentage is being used in applications, and most get burned on the field, causing a large amount of the exhaust gas that pollutes the environment. Herein, we report on the extraction of cellulose nanofibrils (CNF) from the alkali treated WS by a combination of 2,2,6,6-tetramethylpyperidine-1-oxyl (TEMPO)-oxidation and mechanical disintegration method. The crystalline structures, thermal properties, natural charge of the CNF were examined. The resultant nano-building blocks of the CNF was assembled into macroscopic cellulose materials, i.e., film, aerogel, and filament in this work. Furthermore, the morphologies and microstructues as well as other properties of these three kinds of the CNF assemblies were investigated. The obtained CNF and its assemblies showed a potential application in new materials areas. This work explored a new way to utilize the discarded WS instead of being burned.
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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 | 0.000 |
| 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 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".