Modeling Phase Equilibria for the Glycine–NH<sub>4</sub>Cl–Methanol–Water System and Its Application for the Industrial Monochloroacetic Acid Process
Bibliographic record
Abstract
As a continuation of our previous study, this work focuses on the determination and modeling of phase equilibria for the mixed-solvent electrolyte system containing glycine, ammonium chloride (NH 4 Cl), methanol, and water. This electrolyte is used in the monochloroacetic acid (MCA) process for glycine production. The solubilities for the NH 4 Cl–methanol–water and glycine–NH 4 Cl–methanol–water systems were determined from 283.15 to 323.15 K. The MSE model embedded in the OLI platform was modified by regressing experimental data through adjustment of the UNIQUAC and the middle-range interaction parameters. With the new model parameters, solubilities in the quaternary system were predicted with excellent agreement. The average absolute deviations between the prediction and the experimental solubility are 3.46 and 0.54% for glycine and NH 4 Cl, respectively. OLI Stream Analyzer 9.1 was used with this new MSE model to investigate the effect of the methanol composition and temperature on the yield of glycine crystallization in the MCA process. It was found that a methanol mole fraction of 0.65–0.70 at ambient temperatures was optimal for enhancing the theoretical yield of glycine to 96.5% while minimizing the methanol consumption.
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.
How this classification was reachedexpand
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".