Characterization of extruded film based on thermoplastic potato flour
Bibliographic record
Abstract
Abstract Potato flour is abundant and less expensive than starch, though its major component is starch. It would therefore seem to be an attractive and viable source of biomass for biodegradable thermoplastic products. This study prepared thermoplastic potato flour (TPF) and thermoplastic potato starch (TPS) films by extrusion and investigated their properties. A mixture of glycerol and triethyl citrate (25−35% of total weight) was chosen for the plasticizer. Properties of the TPF film, such as mechanical properties, surface hydrophilicity, surface energy, moisture sorption isotherm, and glass transition temperature (Tg), were characterized and compared with TPS film. The results showed that TPF film was comparable to TPS film in many properties. The mechanical properties of the TPF film, including tensile strength, elongation at break, and tensile modulus, were similar in magnitude to TPS film. In addition, TPF film showed lower Tg and surface hydrophilicity, but higher surface wetting capacity than TPS film. Components other than starch in potato flour were believed to have had a plasticization effect on TPF properties. Overall, potato flour demonstrated a comparable capacity for manufacturing thermoplastic film similar to the more expensive starch feedstock. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012
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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".