Estimation of liquid‐liquid equilibrium of type 2 systems (water + valeric acid + monobasic ester or dibasic ester or alcohol) using SERLAS, SERLAS‐modified, and SERLAS‐integrated
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Bibliographic record
Abstract
This paper studies liquid‐liquid equilibrium (LLE) of the type 2 systems (water + valeric acid + dibasic ester or monobasic ester or alcohol) at T = (298.2 ± 0.1) K and p = (101.3 ± 0.7) kPa. Equilibrium distribution of valeric acid onto (water + solvent) two‐phase system is better for more structured diethyl sebacate and ethyl caprylate as compared to less structured diethyl succinate, diethyl malonate, ethyl valerate, and isoamyl alcohol. The two‐phase envelope size and the tie line slope on the phase diagrams are varying as follows: ethyl caprylate > diethyl sebacate > ethyl valerate > diethyl succinate ≈ diethyl malonate > isoamyl alcohol. The SERLAS‐integrated (solvation energy relation for liquid associated systems‐integrated) molecular model with nine physical descriptors, originated from LSER (linear solvation energy relation) principles in conjunction with group‐contribution method, is proposed and applied to the prediction of type 2 LLE properties. By combining SERLAS with UNIFAC‐Dortmund, we are able to get along with a simultaneous impact of both methods for satisfactorily simulating type 2 phase behaviour so long as solvent effects are concerned. SERLAS, SERLAS‐modified, SERLAS‐integrated, and UNIFAC‐original models have been stringently tested for consistency in reproducing phase equilibrium properties with average deviations inferior to 28.8 %, 44.3 %, 21.3 %, and 30.4 %, respectively.
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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 | 0.001 | 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