Benchmarking supramolecular adhesive behavior of nanocelluloses, cellulose derivatives and proteins
Bibliographic record
Abstract
One of the key steps towards a broader implementation of renewable materials is the development of biodegradable adhesives that can be attained at scale and utilized safely. Recently, cellulose nanocrystals (CNCs) were demonstrated to have remarkable adhesive properties. Herein, we study three classes of naturally synthesized biopolymers as adhesives, namely nanocelluloses (CNFs), cellulose derivatives, and proteins by themselves and when used as additives with CNCs. Among the samples evaluated, the adhesion strength was the highest for bovine serum albumin and hydroxypropyl cellulose (beyond 10 MPa). These were followed by carboxymethylcellulose and CNCs (ca. 5 MPa) and mechanically fibrillated CNFs (ca. 2 MPa), and finally by tempo-oxidized CNFs (0.2 MPa) and lysozyme (1.5 MPa). Remarkably, we find that the anisotropy of adhesion (in plane vs out of plane) falls within a narrow range across the bio-based adhesives studied. Collectively, this study benchmarks bio-based non-covalent adhesives aiming towards their improvement and implementation.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".