Effect of High Shear Mixing Parameters and Degassing Temperature on the Morphology of Epoxy-Clay Nanocomposites
Bibliographic record
Abstract
Epoxy-clay nanocomposites were prepared by high shear mixing method using Nanomer I.30E nanoclay as nano-reinforcement in diglycidyl ether of bisphenol A (DGEBA). The effect of mixing speed and time on the nature and degree of clay dispersion were investigated by varying the mixing speed in the range of 500-8000 RPM and mixing time in the range of 15-90 minutes. The effect of degassing temperature on the morphology of the resultant nanocomposites was also studied. Scanning and transmission microscopy (SEM & TEM) along with x-ray diffraction (XRD) have been used to characterize the effect of shear mixing speed, mixing time and degassing temperature on the structure of the resultant nanocomposites. The SEM, TEM and XRD examinations demonstrated that the degree of clay dispersion was improved with increasing the high shear mixing speed and mixing time. The results showed that the optimum high shear mixing speed and mixing time were 6000 rpm and 60 min, respectively. It was observed that the structure of the nanocomposites that have been degassed at 65oC was dominated by ordered intercalated morphology while disordered intercalated with some exfoliated morphology was found for the sample degassed at 100oC for the first 2 hours of the degassing process.
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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 | 0.001 |
| 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 | 0.000 |
| 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".