Permittivity of Mixtures of Saponaria vaccaria and Ethanol–Water Solution for RF Heating Assisted Extraction of Saponins
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Bibliographic record
Abstract
Saponins are used for the treatments of cancers and various infections. The use of radio frequency heating in extracting them from the mixture of particulate Saponaria vaccaria and ethanol-water solution has potentials in pharmaceutical and neutraceutical industries. This technique requires a thorough understanding of the dielectric properties of the mixtures. The dielectric properties of the mixtures were measured over the frequency ranging from 5 to 30 MHz using a computer-controlled precision <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCR</i> meter and a liquid test fixture. The effects of temperature, particle moisture content (MC), frequency, and ethanol concentration (EC) on the dielectric properties of the mixture and penetration depths were investigated at 13.56 and 27.12 MHz. The dielectric constants of the mixtures linearly increased with the particle MC and were more sensitive to it at higher EC of the solution. The dielectric loss factors increased with the particle moisture in somewhat quadratic fashion at 100% EC and linearly at 70%, 40%, and 10% ECs. The dielectric constant and the loss factor linearly increased with the temperature. The increments were more prominent at higher MCs and lower EC. The dielectric spectra of the mixtures monotonically decreased with increasing frequency. The dielectric constants and the dielectric loss factors dropped up to 33% and approximately 50%, respectively, when the frequency was increased from 5 to 10 MHz and then slowly decreased afterward. The penetration depths of the electromagnetic energy within the mixtures decreased with increasing frequency and ranged from 0.06 to 8.83 m at 27.12 MHz. Empirical, semiempirical, and theoretical models for the mixture dielectric properties were tested.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it