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Record W2497403575 · doi:10.1021/bk-2007-0975.ch014

Ionic Liquids as Vehicles for Reactions and Separations

2007· book-chapter· en· W2497403575 on OpenAlexaff
Jason P. Hallett, Philip G. Jessop, Charles A. Eckert, Charles L. Liotta

Bibliographic record

VenueACS symposium series · 2007
Typebook-chapter
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsIonic liquidSolventSolvatochromismCatalysisPolarity (international relations)ChemistryIonic bondingPhase (matter)Combinatorial chemistryOrganic chemistryChemical engineeringIon

Abstract

fetched live from OpenAlex

Ionic liquids possess interesting properties as reaction and processing solvents, but large-scale implementation is hampered by potential difficulties associated with product recovery. We have explored several applications of ionic liquids with a keen focus on the separations accompanying organic synthesis. One exciting new possibility involves the reversible formation of ILs using gaseous C02. This molecular "switch" allows us to turn the polarity of the solvent on and off. We have also developed applications utilizing ILs as phase-transfer catalysts for multiphase organic synthesis; this process enables us to use the solvent as a catalyst, enhancing the reaction efficiency. The solvatochromic behavior of C02/IL systems is also reported, providing insight into the effect of dissolved C02 on the solvent properties, an important consideration for designing C02-based processes using ILs.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.261
Teacher spread0.238 · 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 designNot applicable
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

Citations4
Published2007
Admission routes1
Has abstractyes

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