Structure and Properties of Soy Protein Plastics with ε-Caprolactone/Glycerol as Binary Plasticizers
Bibliographic record
Abstract
We successfully prepared a series of soy protein isolate (SPI) plastics with ε-caprolactone (CL)/glycerol binary plasticizers via extrusion and compression-molding. The chemical reactions among SPI, CL, and glycerol as well as the influence of CL/glycerol content on the microstructure, thermal degradation, and mechanical properties have been investigated using Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), differential scanning calorimetry (DSC), dynamic mechanical thermal analysis (DMTA), thermogravimetric analysis-Fourier transform infrared spectroscopy (TGA-FTIR), and mechanical tests. The results of FTIR, SEM, DSC, and DMTA revealed that CL reacted with protein and glycerol molecules under high-temperature, high-shear, and high-pressure conditions. When the CL content was low (less than 25 wt %), the CL added to the protein matrix was dispersed mainly in the glycerol-rich domains and reacted with glycerol. However, at a higher concentration, the CL predominated in the protein-rich domains and reacted with protein molecules. The chemical reactions led to a significant increase in glass transition and mechanical relaxation temperatures of the glycerol-rich and protein-rich domains. Accordingly, the chemical reactions retarded the volatilization of glycerol and the release of NH 3 and CO 2 and elevated the tensile strength, Young’s modulus, and the water resistance of the soy protein plastic sheets.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".