Prediction and Experimental Measurement of Refractive Index in Ternary Hydrocarbon Mixtures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The physical properties of hydrocarbon mixtures are of great importance in the field of science and technology. Knowing the refractive index of multicomponent liquid mixtures is essential in order to characterize these systems; however, there is a limited amount of experimental data regarding their optical properties. The present study provides precise experimental measurements of the refractive indices of three hydrocarbon compounds: 1,2,3,4-tetrahydronaphthalene (THN), isobutylbenzene (IBB), and dodecane ( n C 12 ). Sixty-three compositions (36 ternaries +27 binaries) were prepared and investigated along with their three pure components using a wide range of concentrations, temperatures and wavelengths. The refractive indices were measured using the multiwavelength Abbemat refractometer. The experimental data were then used to develop and validate new mathematical correlations which can be used to predict the refractive index of ternary mixtures as a function of concentration, temperature, and wavelength. There was a strong correlation between the experimental data and the predictive values with average residual values of ± 1.55·10 –3 . This study also investigated the relative validity of the experimental measurements of the refractive indices with theoretically estimated values using mixing rules and data from the literature. The experimental values were in substantial agreement with the predictive equation values with deviations of ± 2.50·10 –3 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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