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Record W2030597078 · doi:10.1039/b809533g

Organic liquid CO2 capture agents with high gravimetric CO2 capacity

2008· article· en· W2030597078 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy & Environmental Science · 2008
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsQueen's University
FundersPacific Northwest National LaboratoryLaboratory Directed Research and DevelopmentBattelleU.S. Department of Energy
KeywordsGravimetric analysisChemical engineeringChemistryEnvironmental scienceProcess engineeringChromatographyEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

We report a new class of CO2 binding organic liquids that chemically capture and release CO2 much more efficiently than aqueous alkanolamine systems. Mixtures of organic alcohols and amidine/guanidine bases reversibly bind CO2 chemically as liquid amidinium/guanidinium alkylcarbonates. The free energy of CO2 binding in these organic systems is very small and dependent on the choice of base, approximately −9 kJ mol−1 for DBU and Barton's base and +2 kJ mol−1 for 1,1,3,3-tetramethylguanidine. These CO2 capturing agents do not require an added solvent because they are liquid, and therefore have high CO2 capacities of up to 19% by weight for neat systems, and slightly less when dissolved in acetonitrile. The rate of CO2 uptake and release by these organic systems is limited by the rate of dissolution of CO2 into and out of the liquid phase. Gas absorption is selective for CO2 in both concentrated and dilute gas streams. These organic systems have been shown to bind and release CO2 for five cycles without losing activity or selectivity.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.051
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.157
Teacher spread0.150 · 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