Effects of layered silicate structure on the mechanical properties and structures of protein‐based bionanocomposites
Bibliographic record
Abstract
Abstract In this work, a nonconventional protein source of pea protein isolate (PPI) was filled with montmorillonite (MMT) and rectorite (REC) by solution intercalation respectively, and then the reinforced PPI‐based nanocomposites were produced by hot press. The structure and interaction in the nanocomposites were investigated by FTIR, XRD, DSC, DMA, and pH and Zeta‐potential tests whereas the reinforcing effect was verified by tensile test. Furthermore, the origin of enhancing mechanical performances and the effects of layered silicate structure were explored. Although the MMT with lower negative‐charge surface and smaller apparent size of crude particles was easier to be exfoliated completely, the exfoliated REC nanoplatelets with more negative‐charge could form stronger electrostatic interaction with positive‐charge‐rich domains of PPI molecules, and hence produced the highest strength in two series of nanocomposites. In this case, the newly formed hydrogen bonds and electrostatic interaction on the surface of silicate lamellas guaranteed the transferring of the stress to rigid layered silicates. The cooperative effect of newly formed physical interaction between layered silicates and PPI molecules as well as the spatial occupancy of intercalated agglomerates of layered silicates destroyed the original microphase structure of PPI matrix and cleaved the entanglements among PPI molecules. It was not in favor of enhancing the elongation and strength. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".