Facile Preparation of Starch-Based Electroconductive Films with Ionic Liquid
Bibliographic record
Abstract
Here, we discovered that starch could be straightforwardly processed into optically transparent electroconductive films by compression molding at a relatively mild temperature (55 or 65 °C), much lower than those commonly used in biopolymer melt processing (typically over 150 °C). Such significantly reduced processing temperature was achieved with the use of an ionic liquid plasticizer, 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]). A higher [C2mim][OAc] content, lower processing temperature (55 °C), and/or higher relative humidity (RH) (75%) during the sample postprocessing conditioning suppressed the crystallinity of the processed material. The original A-type crystalline structure of starch was eliminated, although small amounts of B-type and V-type crystals were formed subsequently. The starch crystallinity could be linked to the mechanical properties of the films. Moreover, the processing destroyed the original lamellar structure of starch, and the amorphous starch processed with [C2mim][OAc]/water could aggregate on the nanoscale. The films displayed excellent electrical conductivity (>10–3 S/cm), which was higher with a lower processing temperature (55 °C) and a higher conditioning RH (75%). The incorporation of [C2mim][OAc] reduced the thermal decomposition temperature of starch by 30 K, while the formulation and processing conditions did not affect the film thermal stability.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".