Chemical Modeling of the TMA–CO<sub>2</sub>–H<sub>2</sub>O System: A Draw Solution in Forward Osmosis for Process Water Recovery
Bibliographic record
Abstract
Forward osmosis (FO) is an innovative membrane-based process that requires limited external energy input to recover water as it relies on the spontaneous osmotic pressure gradient between a process water stream and a more concentrated solution; the latter is termed a “draw solution”. A suitable draw solution should have properties that allow its solute to be separated into recoverable products that can, in turn, be used to regenerate the initial draw solution with minimum energy requirements. These properties are crucial for the economics of the FO process because the basic energy requirement in FO arises from the separation and regeneration of the draw solution. Recently, it was proposed that such a draw solution can be an aqueous carbonated trimethylamine solution (TMAH:HCO 3 ). In this project, the properties, i.e., composition, pH, and vapor–liquid equilibria (VLE), of the binary TMA–H 2 O and the ternary TMA–CO 2 –H 2 O systems were studied to generate thermodynamic data required to enable accurate speciation calculations by means of OLI-MSE software. Necessary analytical methods to measure accurately total dissolved TMA and total dissolved CO 2 (within 4% error) in aqueous TMAH:HCO 3 solutions were developed. Both VLE data at 50 and 60 °C and pH–composition data at 4 and 25 °C for the ternary TMA–CO 2 –H 2 O system were used to regress the missing binary interaction parameters and improve the model performance. Our resulting databank estimates total pressure ( P Total ), partial pressure of TMA ( P TMA ), partial pressure of CO 2 ( P CO2 ), and pH, with 8, 15, 10, and 1% average absolute relative deviations (AARD), respectively.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".