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Record W2085940937 · doi:10.4155/cmt.12.47

Part 5c: Solvent chemistry: solubility of CO<sub>2</sub>in reactive solvents for post-combustion CO<sub>2</sub>

2012· article· en· W2085940937 on OpenAlexaff
Aravind V. Rayer, Kazi Z. Sumon, Teerawat Sema, Amr Henni, Raphael Idem, Paitoon Tontiwachwuthikul

Bibliographic record

VenueCarbon Management · 2012
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsSolubilitySolventAqueous solutionProcess engineeringChemistryCombustionHildebrand solubility parameterOrganic chemistryChemical engineeringEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Concerns about climate change have propelled research efforts to develop affordable and environmentally benign technologies to capture CO2 from large emission sources, which can subsequently be used either for enhanced oil recovery or stored in other geological storage sites. The study of the solubility of CO2 in solvents is therefore of great interest, both from the theoretical and practical points of view. To screen solvents or to design CO2 capture processes, knowledge of the equilibrium solubility of CO2 in the solvents is necessary. A large body of solubility data of CO2 in aqueous and non-aqueous solutions of prominent industrial amines are available in literature. We present such data along with a description of the experimental techniques and thermodynamic models used. Innovations made to obtain an optimum solubility of CO2 and to minimize the energy cost of a desired CO2 capture system by adopting different kinds of solvents are also reviewed.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0140.005

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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

Citations56
Published2012
Admission routes1
Has abstractyes

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