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Record W2779459670 · doi:10.1039/c7sc04353h

Exploring the role of ionic liquids to tune the polymorphic outcome of organic compounds

2017· article· en· W2779459670 on OpenAlexafffund
Qingying Zeng, Arijit Mukherjee, Péter Müller, Robin D. Rogers, Allan S. Myerson

Bibliographic record

VenueChemical Science · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsMcGill University
FundersCanada Excellence Research Chairs, Government of CanadaDivision of ChemistryCanada Research ChairsNovartisNational Science Foundation
KeywordsIonic liquidOutcome (game theory)Ionic bondingAdverse Outcome PathwayChemistryOrganic chemistryComputational biologyIonBiologyMathematics

Abstract

fetched live from OpenAlex

- have immense possibility in this regard because of their wide flexibility of tunability. More importantly, the interactions among the IL components are completely unique compared to those present in the molecular solvents. In this context, we have chosen tetrolic acid (TA) and isonicotinamide (INA), which showed solution-structure link in molecular solvents in the past, as probes to investigate the role of imidazolium based ionic liquids in the polymorphism of these two systems and whether the different solute-solvent interactions in ILs affect the polymorphic outcome. It is observed that the selected imidazolium-based ILs, with varying anion basicity have influenced the crystallization outcome by the interaction between ILs and model compounds. Later, we have utilized the concept of double salt ionic liquids (DSIL) for INA, a penta-morphic system, to investigate the variation in the polymorphic outcome. This approach helped to obtain the forms that were otherwise inaccessible in 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 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 score0.006
Threshold uncertainty score0.365

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.065
GPT teacher head0.272
Teacher spread0.207 · 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

Citations49
Published2017
Admission routes2
Has abstractyes

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