Thermal transport, thermomechanical, and dielectric properties of chalcogenide Se<sub>98–</sub><sub><i>x</i></sub>Ag<sub>2</sub>In<sub><i>x</i></sub> (<i>x</i> = 0, 2, 4, 6) system
Bibliographic record
Abstract
The present work reports a detailed study of some physical properties of some novel glasses of Se98–xAg2Inx (x = 0, 2, 4, 6) system. Measurements of thermal transport properties (i.e., thermal conductivity, κ, and thermal diffusivity, χe) have been carried out using the transient plane source technique. Specific heat measurements have been done by differential scanning calorimetry. Thermomechanical properties (i.e., Vickers hardness, Hv, and modulus of elasticity, E) have been evaluated by the indenter test. The minimal energy for formation of microvoids, Eh, and microvoids volume, Vh, of the previously mentioned glassy system are discussed in terms of microhardness, Hv. Temperature and frequency dependence of dielectric constant, ε1, and dielectric loss, ε2, for the same system were measured in the frequency (50 Hz – 1000 kHz) and temperature (303–338 K) range. The experimental results illustrate that the values of dielectric constant, ε1, and dielectric loss, ε2, are decreased with frequency and increased with temperature. The maximum barrier height, Wb, is calculated using the dielectric measurements according to the Guintini equation. The morphology and microstructural analysis of as-prepared alloys are confirmed by X-ray diffraction, scanning electron microscope, and transmission electron microscope.
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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".