Dynamic Column Breakthrough and Process Studies of High-Purity Oxygen Production Using Silver-Exchanged Titanosilicates
Bibliographic record
Abstract
Many medical and industrial applications require high-purity oxygen. Because of the similar physical properties of oxygen and argon, this separation is very challenging, and very few commercial adsorbents offer the ability to separate the two gases. Silver-exchanged titanosilicates (Ag-ETS-10) have the potential to separate these gases based on their adsorption affinities. In this work, adsorption isotherms of O 2, Ar, and N 2 on Ag-ETS-10 extrudates have been measured using a volumetric technique and described using a Langmuir isotherm. Single, binary, and ternary breakthrough profiles were measured using a laboratory-scale dynamic column breakthrough apparatus. These profiles have been modeled by writing mass and energy balances that are solved using the finite volume technique. The model was able to predict the experimental profiles to a high degree of accuracy. A simple vacuum swing adsorption process was simulated using mathematical models to demonstrate the potential of the material to produce high-purity oxygen. Multiobjective optimization to maximize O 2 purity and recovery from a feed containing 95% O 2 and 5% Ar revealed that purities in excess of 99.0% can be achieved at a recovery of 11.35%.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".