Effect of Particle Size on the Dielectric Properties of Sodium Potassium Niobate -Portland Cement Composites
Bibliographic record
Abstract
In this research, the effect of sodium potassium niobate, (Na0.5K0.5)NbO3 (NKN) particle size on the dielectric properties of 0-3 non lead based piezoelectric cement based composites were investigated. NKN of various particle sizes (75, 225 and 450 μm) were used at 50% by volume to produce the composites. Dielectric properties at various frequencies (0.1–20 kHz) were investigated. The results showed that the dielectric values of NKN-PC composites increased with increasing NKN particle size where ε r at 1 kHz are 158.60 and 191.21 for composites with 75 μm and 450 μm NKN particle size respectively. The dielectric loss (tanδ) was found to reduce with increasing NKN particle size and the tan δ value was lowest at 0.39 for composite with 450 μm NKN particle size.
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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".