MétaCan
Menu
Back to cohort

Excess Volume of Binary Mixtures of Water (Methanol or Ethanol) with an Ionic Liquid [EEIM][DEP] or [BEIM][DEP] at 1 atm and (293.15 to 333.15) K

2014· article· en· W2084269897 on OpenAlexvenueno aff
Hongyan Song, Yin-Hui Gong, Xuemei Jiang, Chun-Xi Lib

Bibliographic record

VenueJournal of Applied Solution Chemistry and Modeling · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMethanolChemistryEthanolVolume (thermodynamics)Ionic liquidBinary numberIonic bondingChromatographyAnalytical Chemistry (journal)ThermodynamicsOrganic chemistryIonPhysics

Abstract

fetched live from OpenAlex

Densities were measured for the binary mixtures of water (methanol or ethanol) and an ionic liquid (IL) 1,3-diethylimidazolium diethylphosphate [EEIM][DEP] or 1-n-butyl-3-ethylimidazolium diethylphosphate [BEIM][DEP] at 1 atm and (293.15 to 333.15) K using a vibrating-tube densimeter. The molecular volume, standard entropy, and lattice energy of the two ILs were estimated with the Glasser theory. The excess volumes are negative for all binary mixtures studied in the whole composition range, and reach to the maximum at the mole fraction of IL being around 0.3. Besides, they decrease with increasing temperature for the aqueous solution of ILs, whilst a reverse trend is found for the IL solutions of methanol or ethanol at any concentration. The excess molar volumes were correlated successfully by a five-parameter polynomial equation as a function of temperature and mole fraction of IL with average absolute relative deviation (ARD) of density within 0.02%.

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 score0.134
Threshold uncertainty score0.567

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 head0.020
GPT teacher head0.244
Teacher spread0.224 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Solution Chemistry and ModelingSame topicIonic liquids properties and applicationsFrench-language works237,207