Polyamide 12 (PA12)/clay nanocomposites fabricated by conventional extrusion and water‐assisted extrusion processes
Bibliographic record
Abstract
ABSTRACT This work aims at comparing the efficiency of three melt compounding methods for preparing polyamide 12 (PA12)/untreated clay composites. Conventional extrusion was compared with two water‐assisted extrusion methods previously described in the literature and respectively involving injection of water in the polymer/clay stream or injection of aqueous clay slurry in the polymer stream. The dispersion of the clay in the composites was analyzed at the microscale and at the nanoscale using microscopy (optical and electronic) and wide angle X‐ray diffraction (WAXD). The tensile properties of the composites were evaluated. The results showed that injection of aqueous clay slurry in the polymer stream was the most efficient method for preparing PA12/untreated clay composites, although clay particles remained mainly dispersed at the microscale. This method allowed for a drastic size reduction of the microparticles, accompanied by enhancements of ca. +10 % in tensile modulus and tensile strength (compared with equivalent composites obtained by conventional extrusion). The influence of the pH of the aqueous clay slurry was also investigated: neutralization of the clay slurry generated finer dispersions, probably resulting from a better pre‐exfoliation of the clay in the water medium. PA12/organophilic clay composites were also prepared as control samples. When an adequate surface treatment was selected, nanoscale dispersion of the clay platelets was easily achieved. In this case, composites prepared by conventional extrusion showed overall similar properties as their equivalents prepared using injection of water in the polymer/clay stream. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 130: 1959–1974, 2013
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".