Separation of carbon dioxide and nitrogen gases using novel composite membranes
Bibliographic record
Abstract
Global warming is the major environmental issue caused by greenhouse gases, especially CO 2 . This demands urgent action to reduce or offset CO 2 emission from power plants, which could be done using facilitated transport membranes (FTMs). In this context, CO 2 selective carriers were prepared by blending polyvinyl alcohol (PVA) with three amines: ethylenediamine (EDA), diethylenetriamine (DETA), and triethylenetetramine (TETA). Then, the composite membranes were prepared using PVA–amine blend as the separation layer and ceramic candle filters as the support layer. The fabricated membrane was characterized by Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). Furthermore, the effect of amine species, effect of TETA concentration, cross-linking agent content, pressure difference, and the thickness of the membrane on the permeance and selectivity of CO 2 over N 2 were investigated. The permeance and selectivity of CO 2 through the membranes were in the following order: TETA > DETA > EDA. This order is related to the number of nitrogen atoms per amine molecule, which can be correlated to loading capacity and, consequently, to amine reactivity with CO 2 . Under optimized conditions, for a pure gas experiment, the maximum permeance of 6.9 GPU for CO 2 gas and selectivity of 50 over N 2 was obtained, whereas in the CO 2 /N 2 gas mixture, the maximum permeance of 8.6 GPU and selectivity of 98 was obtained. The membrane was found to be stable for 264 h.
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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 | 0.000 | 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) | 0.000 | 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".