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Record W2591855097 · doi:10.5772/65763

Synergistic Effect on CO2 Capture by Binary Solvent System

2017· book-chapter· en· W2591855097 on OpenAlexfundno aff
Quan Zhuang, Bruce Clements

Bibliographic record

VenueInTech eBooks · 2017
Typebook-chapter
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsnot available
FundersAustralian GovernmentUniversity of Ottawa
KeywordsPiperazineChemistrySolventPotassium carbonateAbsorption (acoustics)Binary systemInorganic chemistryChemical engineeringOrganic chemistryBinary numberMaterials science

Abstract

fetched live from OpenAlex

CO2 absorption into a binary solvent system was studied using a batch‐mode gas/liquid absorption apparatus. The binary system composed of potassium carbonate (K2CO3) and piperazine (PZ) showed a strong synergistic effect, whereby the binary solvent performed better than either of the individual solvents for CO2 absorption. The other pairs of solvents tested (K2CO3/monoethanolamine (MEA) and K2CO3/NaOH) showed no synergistic effects. The results indicate that this synergistic effect only occurs with specific pairs of solvents. The mechanism for the synergistic effect is postulated that the activated CO2 on PZ migrates to K2CO3, or a more reactive intermediate complex between K2CO3 and PZ is formed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.778
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
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 head0.009
GPT teacher head0.204
Teacher spread0.196 · 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.

Study designBench or experimental
Domainnot available
GenreOther

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

Citations2
Published2017
Admission routes1
Has abstractyes

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