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Record W2082108050 · doi:10.1021/ie9002238

On the Predictive Ability of the New Thermodynamics of Electrolyte Solutions

2009· article· en· W2082108050 on OpenAlexafffund
Grażyna Wilczek-Vera, Juan H. Vera

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2009
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsMcGill University
FundersMcGill University
KeywordsThermodynamicsElectrolyteActivity coefficientConsistency (knowledge bases)Osmotic coefficientWork (physics)Ionic bondingChemistryAqueous solutionIonSalt (chemistry)Physical chemistryComputer sciencePhysics

Abstract

fetched live from OpenAlex

This work highlights the main elements of the new thermodynamic approach to electrolyte solutions and demonstrates its ability to make predictions for mixed salt systems. After a review of the state of affairs before the measurement of activities of individual ions, experimental set-ups used for these measurements are described and the essential elements of different methods used to reduce the data are discussed. The results of experiments carried to test a possible bias introduced by uncertainty in the values of the junction potential are emphasized. It is purported that the thermodynamic treatment proposed by Lin and Lee is of general application and ensures the thermodynamic consistency of correlations previously proposed for the individual ionic activities. It is shown that the use of a more complex form for the contribution of long-range interactions to ionic activities leads to a simpler form of the osmotic coefficient. As an example of application, the predictions of the equilibrium pressure over NaCl + KCl, NaBr + KBr, and NaCl + CaCl 2 aqueous solutions, at different temperatures and compositions, are compared with independently measured experimental data.

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)0.003
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 score0.051
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.061
GPT teacher head0.287
Teacher spread0.226 · 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

Citations20
Published2009
Admission routes2
Has abstractyes

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