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Record W2345020286 · doi:10.1021/acs.iecr.6b01560

Dynamic Column Breakthrough and Process Studies of High-Purity Oxygen Production Using Silver-Exchanged Titanosilicates

2016· article· en· W2345020286 on OpenAlexafffund
Sayed Alireza Hosseinzadeh Hejazi, Arvind Rajendran, James A. Sawada, Steven M. Kuznicki

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2016
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaHelmholtz-Alberta Initiative
KeywordsAir separationAdsorptionTernary operationVolume (thermodynamics)OxygenArgonChemistryRefining (metallurgy)Work (physics)Pressure swing adsorptionMaterials scienceChromatographyChemical engineeringProcess engineeringAnalytical Chemistry (journal)ThermodynamicsOrganic chemistryComputer sciencePhysical chemistry

Abstract

fetched live from OpenAlex

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%.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.127
GPT teacher head0.362
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2016
Admission routes2
Has abstractyes

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