MICROSTRUCTURE AND EXFOLIATION MECHANISM OF CLAY PARTICLES OF EPOXY/CLAY NANOCOMPOSITES UNDER EXTERNAL SHEARING FORCE
Bibliographic record
Abstract
Different processing methods such as magnetical stirring,high-speed emulsifying and homogenizing and ball milling,were used to homogenously disperse the clay agglomerates and facilitate their exfoliation in epoxy/clay nanocomposites.The mechanical properties and effect of external shearing force on the exfoliation of organic clay modified with organic amine,quaternary ammonium salts and the combination of quaternary ammonium salts and meta-xylylenediamine (MXDA) were investigated.It was found that,for the general stirring,only partially exfoliated structure for the small clay particles or the external layers of large clay agglomerates were obtained.While the fine exfoliation for the external and central layers can be easily achieved by exerting vigorous shearing force,and the catalytic role of acid primary alkylammonium is not the key influencing the exfoliation of clay in epoxy matrix.The impact strength and flexural strength of epoxy/clay nanocomposites can be dramatically improved,which was about 50% and 8% higher than those of the pristine epoxy,respectively.The degree of exfoliation of clay particles will be substantially determined by the pulverization of the clay agglomerates.The smaller the size of clay particles,the better the dispersion and exfoliation of clay layers are, and a simultaneous outward shift of the external and central layers occurs.
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 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".