Influence of Citric Acid on the Properties of Glycerol‐plasticized dry Starch (DTPS) and DTPS/Poly(lactic acid) Blends
Bibliographic record
Abstract
Abstract In the presence of citric acid (CA), one‐step extrusion processing is used to prepare poly(lactic acid)/thermoplastic dry starch (PLA/DTPS) blends (50/50, %, w/w) in a single‐screw extruder. The rheological study proves that CA decreases the viscosity of both DTPS and of DTPS/PLA blends. The low viscosity increases the dispersion and decreases the interfacial tension between DTPS and PLA, as shown by scanning electron microscopy (SEM). In the presence of CA, the tensile strength of DTPS/PLA reaches 41 MPa—similar to that of pure PLA—because of improved dispersion and compatibility. At the same time, CA increases not only the degradation of starch, but also the interaction between DTPS and PLA, as detected by Fourier transform infrared (FTIR) spectroscopy. The blend containing CA has a higher thermal stability. The water absorption of DTPS and DTPS/PLA blends is also studied.
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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".