Effect of nanoclay concentration level on the electrical properties of polypropylene under electron irradiation in a SEM
Bibliographic record
Abstract
For studying the electrical properties (charge trapping, transport and secondary electron emission) of the polypropylene-based nanocomposites with different contents of natural clay, the specimens were submitted to electron irradiation of a scanning electron microscope. A device, suitably mounted on the sample holder of the scanning electron microscope, was used to measure two currents (i.e. leakage and displacement currents) induced in the polypropylene-based nanocomposites (polymer nanocomposites) under electron irradiation. The evolution of trapped charge during irradiation for each type of studied polymer nanocomposites is deduced. The amount of trapped charge at the steady state is also determined by measuring the change of secondary electron image size associated to the electron trajectory simulation. It is found, surprisingly, that not only the leakage current increases as a function of clay loading level but also trapped charge. However, this could be related to the increase of conductivity in one hand and to proliferation of interfaces between nanoparticles and neighbouring materials on the other hand. These two processes play crucial role in controlling the carrier transport (through polymer nanocomposites or/and along its surface) closely related to the charge storage and leakage current. Additional experiment using dielectric spectroscopy were performed to show the effect of clay concentration in changing the dielectric relaxation behaviour and to evidence the existence of interfaces between nanoparticles and polymer. The secondary electron emission during electron irradiation is also studied through the total electron yield that is deduced by correlating the measured leakage and displacement currents.
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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".