Phase Equilibria for the Glycine–Methanol–NH<sub>4</sub>Cl–H<sub>2</sub>O System
Bibliographic record
Abstract
An investigation of the phase equilibria of the glycine–methanol–NH 4 Cl–H 2 O system was carried out with the objective of optimizing the monochloroacetic acid (MCA) process for the production of glycine. Phase equilibrium of the glycine–NH 4 Cl–H 2 O system at temperatures over the range of 283.2–353.2 K was determined for concentrations ranging up to the multiple saturation points. The solubilities of both glycine and NH 4 Cl were found to increase with increasing temperature, as well as with increasing concentration of other solutes. The Bromley–Zemaitis model for ions and the Pitzer formulation for glycine neutral species implemented in the OLI platform were used in the regression of the experimental solubilities. The average absolute deviations between the regressed solubility values and the experimental data were found to be 1.4% for glycine and 0.93% for NH 4 Cl. Three binary interaction parameters of the Pitzer formulation were newly obtained and coupled with the Bromley–Zemaitis parameters documented in OLI’s databank to predict the multiple saturation points of the system. Additionally, the solubility of glycine in methanol–H 2 O mixtures was also measured from 283.2 to 323.2 K, and a sharp decline was observed as a function of the content of methanol. Such thermodynamic information is definitely useful for improving the existing industrial process, as well as providing fundamentals for the development of new glycine production processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".