Thermodynamic Modeling of Multi-Staged Extraction Systems for Chiral Separations through Coupled Analysis of Species Equilibria and Mass Transfer
Why this work is in the frame
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Bibliographic record
Abstract
A flexible and comprehensive model for predicting and optimizing separations of racemates of amino acids and other chiral metabolites in liquid-liquid multi-staged extraction systems is presented. Enantiomer partition coefficients are computed along the extraction path using multiple chemical equilibria theory and measured equilibrium formation constants for every complex formed in the two phases. The large number of speciation reactions typically occurring in ligand-exchange extraction systems requires the development of a robust numerical algorithm, and we present a method to rapidly and accurately solve the large nonlinear set of governing equations. Model performance is assessed through comparison to data for continuous extraction of various racemates within a series of hollow-fiber membrane modules. For each extraction, a chiral-ligand exchange selector molecule is solubilized in the organic phase flowing countercurrent to the aqueous phase into which the racemate is loaded. Enantiomer eluent profiles predicted at different conditions are in very good agreement with experiment. Through its predictive power, the model provides a useful in silico platform for optimizing these complex separations, and model results demonstrating this capability are presented.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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