Multifunctional nanocrystalline cellulose ionogels toward tough and sustainable materials
Bibliographic record
Abstract
Design and fabrication of sustainable cellulose-based ionogels with good mechanical properties have attracted increasing research interest; however, most current developed ionogels show limited processibility and functionality. Here, we report the development of tough and multifunctional ionogels by mixing nanocrystalline cellulose (NCC) into ionic liquid (IL), where the partial solvation of NCCs enables the formation of ionogels with varied NCC loadings. Partially solvated NCCs (PS-NCCs) have high-crystallinity domains offering rigidity, surrounded by cellulose chains enabling flexibility and energy dissipation. The NCC ionogel can achieve a high Young’s modulus (∼44 MPa), toughness (∼34 kJ m−2), and stretchability (∼870% strain), while also exhibiting thermal-triggered self-healing, stiffness transition, shape memory, and conductivity-changing properties. The NCC ionogels show their potential to work as multifunctional platforms for advanced applications, including grippers, temperature sensors, and three-dimensional printing. In addition, the IL in the ionogel is recyclable, and the ionogel can be degraded in natural environmental conditions, further enhancing its sustainability.
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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) | 0.001 | 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".