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Record W2053351351 · doi:10.1002/cjce.5450800427

An Aqueous Phase Equilibrium Calculation Algorithm

2002· article· en· W2053351351 on OpenAlexafffundvenue
Ajay Makkuni, Aaron Phoenix, Sohrab Rohani

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2002
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsWestern UniversityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTangentPhase equilibriumWork (physics)AlgorithmAqueous solutionPhase (matter)Chemical equilibriumAccelerationSolubilityPlane (geometry)Computer scienceThermodynamicsChemistryPhysicsMathematicsPhysical chemistryClassical mechanicsGeometry

Abstract

fetched live from OpenAlex

Abstract A multiphase chemical equilibrium algorithm is developed which can be used with aqueous systems. The algorithm uses an average chemical potential for each species as a reference chemical potential. Incipient phases can be identified and their proximity to appearance can be determined through their tangent plane distance. Illustrative examples include the calculation of CaSO 4 solubility and the calculation of vapour pressures above an SO 2 ‐NaCl‐H 2 O system, including the prediction of a three‐phase equilibrium. The algorithm proved robust and versatile. The appearance of incipient phases was easily tracked. Future work needs to be done to optimize damping/acceleration coefficients in the calculations.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.592

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 science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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

Citations2
Published2002
Admission routes3
Has abstractyes

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