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Record W2003988707 · doi:10.1021/es071824k

Medium-Pressure Clathrate Hydrate/Membrane Hybrid Process for Postcombustion Capture of Carbon Dioxide

2007· article· en· W2003988707 on OpenAlexafffund
Praveen Linga, Adebola Adeyemo, Peter Englezos

Bibliographic record

VenueEnvironmental Science & Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClathrate hydrateTetrahydrofuranHydrateChemistryCarbon dioxideCrystallizationThermodynamicsProcess (computing)Chemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

This study presents a medium-pressure CO2 capture process based on hydrate crystallization in the presence of tetrahydrofuran (THF). THF reduces the incipient equilibrium hydrate formation conditions from a CO2/N2 gas mixture. Relevant thermodynamic data at 0.5, 1.0, and 1.5 mol % THF were obtained and reported. In addition, the kinetics of hydrate formation from the CO2/N2/ THF system as well as the CO2 recovery and separation efficiency were also determined experimentally at 273.75 K. The above data were utilized to develop the block flow diagram of the proposed process. The process involves three hydrate stages coupled with a membrane-based gas separation process. The there hydrate stages operate at 2.5 MPa and 273.75 K. This operating pressure is substantially less than the pressure required in the absence of THF and hence the compression costs are reduced from 75 to 53% of the power produced for a typical 500 MW power plant.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.005
GPT teacher head0.223
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations227
Published2007
Admission routes2
Has abstractyes

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