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Record W2275399744 · doi:10.1002/cssc.201501654

Switchable‐Hydrophilicity Solvents for Product Isolation and Catalyst Recycling in Organocatalysis

2016· article· en· W2275399744 on OpenAlexaff
Julia Großeheilmann, Jesse R. Vanderveen, Philip G. Jessop, Udo Kragl

Bibliographic record

VenueChemSusChem · 2016
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsQueen's University
FundersDeutsche Forschungsgemeinschaft
KeywordsCatalysisYield (engineering)MicroreactorExtraction (chemistry)ChemistryOrganic chemistryChemical engineeringAmine gas treatingOrganocatalysisMaterials scienceEnantioselective synthesis

Abstract

fetched live from OpenAlex

Switchable-hydrophilicity solvents (SHSs) are solvents that can switch reversibly between a water-miscible state to a state that forms a biphasic mixture with water. In this case study, SHSs have been studied for easy product/catalyst separation as well as catalyst recycling. A series of tertiary amine SHSs have been identified for the extraction of the hydrophilic product from the postreaction mixture. Here, we determined high extraction efficiencies for the product (>84%) and low extraction rates for the catalyst (<0.1%). With the catalyst recycling experiments, we isolated the product in high purity (>98%) without further purification steps. At the same time, the catalyst was reused without any loss of activity (>91% enantiomeric excess, >99% yield) four times. Furthermore, we optimized the extraction efficiency by working with a microextractor. In addition, with the use of a falling-film microreactor, we obtained the product with high enantioselectivity by working at ambient conditions.

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 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 score0.253
Threshold uncertainty score0.517

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 head0.013
GPT teacher head0.230
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 teacher head, 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

Citations32
Published2016
Admission routes1
Has abstractyes

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