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Record W1989001351 · doi:10.1021/ie000828u

A Chemical Equilibrium Equation of State Model for Elemental Sulfur and Sulfur-Containing Fluids

2001· article· en· W1989001351 on OpenAlexafffund
Robert A. Heidemann, Aaron Phoenix, Kunal Karan, Leo A. Behie

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2001
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSulfurHydrogen sulfideChemistrySour gasMethaneSulfideEquation of stateNitrogenAcid gasHydrogenChemical equilibriumCarbon fibersThermodynamic equilibriumSulfur dioxideThermodynamicsNatural gasInorganic chemistryOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

The phase behavior of natural gases containing elemental sulfur has been modeled using a chemical equilibrium model and the Peng−Robinson equation of state. Sulfur in the fluid phases is modeled as a mixture of eight species, S 1 through S 8, and reactions of each with hydrogen sulfide to form eight different sulfane species are anticipated. A proposal is made for constructing the Peng−Robinson parameters for all species from the parameters for source substances including S 8 and H 2 S and interaction parameters only between the source substances. A separate model is used for sulfur as a solid. Comparisons are made with data for pure sulfur and for sulfur in contact with a number of gas mixtures containing hydrogen sulfide, carbon dioxide, methane, and nitrogen. The equilibrium sulfur content of the gases is well predicted over a wide range of gas composition, temperature, and pressure.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.096
GPT teacher head0.316
Teacher spread0.219 · 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 designTheoretical or conceptual
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

Citations47
Published2001
Admission routes2
Has abstractyes

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