Biocomposites from Thermoplastic Postindustrial Waste Starches Filled with Mineral Fillers for Single‐Use Flexible Packaging
Bibliographic record
Abstract
Abstract Plasticized starch (PS) materials hold a fundamental role in the design of novel biodegradable and compostable plastics aimed to reduce global single‐use plastic wastes. This work exemplifies the plasticization of postindustrial waste wheat starch (pWWS) and postindustrial corn starch (pWCS) with a comparison to food‐grade corn starch (pCS) by introducing technical waste glycerol (25%) along with urea (5%) and water. The PS (30%) is blended with 70% poly(butylene adipate‐co‐terephthalate) (PBAT) to design a matrix with optimized mechanical properties. As a result, the inclusion of pWCS and pCS shows similar impact strength and melt flow index (MFI) values. Further, the mineral fillers, i.e., talc and calcium carbonate (CaCO3) (25%), are introduced into the PBAT/PS (70%/30%) matrix to explore the effect on MFI, mechanical, thermal, and morphological properties. Scanning electron microscopy analysis reveals good dispersion of PS particles and mineral fillers into the PBAT. Adding talc into the PBAT/pWWS and PBAT/pCS blends shows significantly higher modulus (≈134% and ≈105%, respectively) and heat deflection temperature (HDT) (7.8% and 9.3%, respectively). The addition of 25% CaCO3 results in the impact strength of PBAT/pWWS being improved by ≈20%. Due to talc's lamellar platelet structure and better dispersion, the inclusion of talc into the PBAT/PS blends shows improved rheological properties compared to that of CaCO3.
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 | 0.000 | 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".