Experimental Study and Modeling of Flow Behavior and Orientation Kinetics of Layered Silicate/Polypropylene Nanocomposites in Start-up of Shear Flows
Bibliographic record
Abstract
Abstract Effects of organoclay contents on the startup flow properties of layered nano-scale particles in the simple shear mode are investigated. The addition of small amounts of nanoclays to polypropylene melts was found to dramatically change the flow characteristics and creates stress overshoots at large shear rates. A rheological model, initially developed for studying the motion of a group of symmetric ellipsoid particles in viscoelastic fluids was used to describe the orientation state of the uniformly dispersed suspensions of layered silicate in polypropylene melts. The effects of shear, particle loadings, particle interactions, flow reversal and rest time after cession of shear are studied and discussed according to our experimental observations and model predictions. It is shown that another diffusion term in the governing equation for the particles can be used to predict the properties by applying the rest time which was found to change the orientation of particles and shifts it to more isotropic microstructures. The experimental results of the startup viscosity are reasonably well predicted by the model at the three shear rates tested.
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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 | 0.000 |
| 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".