Ionic Liquids as Designed, Multi-Functional Plasticizers for Biodegradable Polymeric Materials: A Mini-Review
Bibliographic record
Abstract
Measures to endorse the adoption of eco-friendly biodegradable plastics as a response to the scale of plastic pollution has created a demand for innovative products from materials from Nature. Ionic liquids (ILs) have the ability to disrupt the hydrogen bonding network of biopolymers, increase the mobility of biopolymer chains, reduce friction, and produce materials with various morphologies and mechanical properties. Due to these qualities, ILs are considered ideal for plasticizing biopolymers, enabling them to meet a wide range of specifications for biopolymeric materials. This mini-review discusses the effect of different IL-plasticizers on the processing, tensile strength, and elasticity of materials made from various biopolymers (e.g., starch, chitosan, alginate, cellulose), and specifically covers IL-plasticized packaging materials and materials for biomedical and electrochemical applications. Furthermore, challenges (cost, scale, and eco-friendliness) and future research directions in IL-based plasticizers for biopolymers are discussed.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".