Regenerating Membrane Contactors for Solvent Absorption
Bibliographic record
Abstract
Membrane contactors are a hybrid technology that incorporates the advantages of both solvent absorption and membrane separation. Porous and asymmetric composite membrane contactors have been studied for CO 2 absorption, and both configurations are susceptible to pore wetting. This results in a significant reduction in the mass transfer efficiency. As such, regeneration methods to remove entrained liquids from the contactors are of interest. In this work, four regeneration protocols are trialled for a porous poly tetrafluoroethylene (PTFE) contactor and a thin film composite poly(1-trimethylsilyl)-1-propyne (PTMSP) contactor. It was found that air and vacuum drying at elevated temperatures increased the overall mass transfer coefficient of both contactors compared to the wetted state, but did not return either to their original performance. In addition, both contactors experienced rapid rewetting of the pores. Prewashing with methanol before air drying at elevated temperature produced the greatest improvement in overall mass transfer for the regenerated contactors. This was attributed to methanol miscibility with the water in the pores reducing the capillary pressure experienced during drying, as well as methanol swelling the PTMSP layer. However, original functionality was not achieved for either contactors and both continued to experience wetting over time, though at a slower rate than with non-methanol wash regeneration protocols.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".