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Record W2103207805 · doi:10.1351/pac200072122275

Influence of chloride, water, and organic solvents on the physical properties of ionic liquids

2000· article· en· W2103207805 on OpenAlexfundno aff
Kenneth R. Seddon, Annegret Stark, María-José Torres

Bibliographic record

VenuePure and Applied Chemistry · 2000
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilQueen's UniversityBP GlobalEuropean CommissionRoyal Academy of Engineering
KeywordsChemistryIonic liquidViscosityChlorideImpurityIonic bondingMole fractionInorganic chemistryOrganic chemistryChemical engineeringIonPhysical chemistryCatalysisThermodynamics

Abstract

fetched live from OpenAlex

Abstract We report here the first systematic study of the effect of impurities and additives (e.g., water, chloride, and cosolvents) on the physical properties of room-temperature ionic liquids. Remarkably, it was discovered that the viscosity of mixtures was dependent mainly on the mole fraction of added molecular solvents and only to a lesser extent upon their identity, allowing viscosity changes during the course of a reaction to be entirely predictable. While the addition of such molecular solvents decreases the viscosity and density, chloride impurities, arising from the preparation of the ionic liquids, increase viscosity dramatically. The commonly used methods of preparation were validated with respect to chloride impurity.

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)0.002
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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

Citations2,246
Published2000
Admission routes1
Has abstractyes

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