Diffusion of CH4 and N2 in Barium-Exchanged Reduced Pore Zorite (Ba-RPZ) and Zeolite 4A
Bibliographic record
Abstract
Barium-exchanged reduced pore zorite (Ba-RPZ) is a titanosilicate molecular sieve that is able to separate CH4 from N2 based on their relative molecular sizes. A detailed study of N2 and CH4 adsorption equilibrium and diffusion on Ba-RPZ was completed using low and high-pressure volumetry. Adsorption equilibrium data for Ba-RPZ from limiting vacuum to 1.2 bar were measured at 30, 40, and 50° C for CH4 and at 30, 50, and 70° C for N2. Constant volume uptake experiments were conducted to estimate the diffusivities of CH4 at 30, 40, and 50° C and N2 -20, -10, and 0° C. Similar experiments were carried out with zeolite 4A to validate the methods used in this study. On the one hand, the transport of N2 in Ba-RPZ was found to be controlled by diffusion in the micropores. On the other hand, the transport of CH4 in Ba-RPZ was described by a dual-resistance model, including a barrier resistance and micropore diffusional resistance. Both the barrier and micropore diffusion coefficients demonstrated concentration dependence. While the micropore diffusion constant followed Darken's relationship, the barrier resistance did not. A concentration-dependent dual-resistance diffusion model for methane was constructed and validated using experimental data across a range of pressures and temperatures. The concentration-dependent dual-resistance model was able to describe the complex diffusion behaviour methane displays as it progressed from the dual-resistance controlled region to the micropore-controlled region of the isotherm. The calculated CH4/N2 kinetic selectivity of Ba-RPZ was shown to be significantly larger than the current benchmark material for CH4/N2 separation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".