Polymer based membranes for propylene/propane separation: CMS, MOF and polymer electrolyte membranes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<abstract> <p>Propylene/propane separations are generally performed by distillation which are energy intensive and costly to build and operate. There is therefore high interest to develop new separation technologies like membrane modules. In our previous paper, we collected, analyzed and reported data for neat polymers and mixed matrix membranes (MMM) based on flat and hollow fiber configurations for propylene/propane separations. In this second part, we collected the data for carbon molecular sieving (CMS) membranes from polymer pyrolysis reaction and metal-organic framework (MOF) membranes from different fabrication methods, as well as data on facilitated transport membrane-polymer electrolyte membranes (PEM). CMS membranes show great potential for C<sub>3</sub>H<sub>6</sub>/C<sub>3</sub>H<sub>8</sub> separation with an optimum pyrolysis temperature around 500–600 ℃. However, physical aging is a concern as the micro-pores shrink over time leading to lower permeability. The performance of MOF membranes are above the 2020 upper bound of polymer-based membranes, but have limited commercial application because they are fragile and difficult to produce. Finally, facilitated transport membranes show excellent propylene/propane separation performance, but are less stable compared to commercial polymeric membranes limiting their long-term operation and practical applications. As usual, there is no universal membrane and the selection must be made based on the operating conditions.</p> </abstract>
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it