MétaCan
Menu
Back to cohort
Record W2330887416 · doi:10.1021/je100729t

Ion Association in Dilute Aqueous Magnesium Sulfate and Nickel Sulfate Solutions Under Hydrothermal Conditions by Flow Conductivity Measurements

2011· article· en· W2330887416 on OpenAlexafffund
Melerin Madekufamba, Peter R. Tremaine

Bibliographic record

VenueJournal of Chemical & Engineering Data · 2011
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsUniversity of Guelph
FundersUniversity of GuelphUniversity of Delaware
KeywordsChemistryNickelSulfateIon-associationAqueous solutionMagnesiumInorganic chemistryEquilibrium constantConductivityAnalytical Chemistry (journal)IonSolubilitySolubility equilibriumSolventPhysical chemistryChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Electrical conductivities of very dilute aqueous solutions of magnesium sulfate and nickel sulfate (∼ 10 −3 mol·kg −1 ) were measured at temperatures from (398.15 to 548.15) K and from (398.15 to 498.15) K, respectively, with an alternating current (AC) conductivity flow cell at a pressure of 18.62 MPa. The resulting conductivity data were modeled using the Fuoss−Hsia−Fernández−Prini (FHFP) conductance equations together with the appropriate activity coefficient expressions, to obtain equilibrium constants for the ion association reactions: Mg 2+ (aq) + SO 4 2− (aq) ⇌ MgSO 4 o (aq) and Ni 2+ (aq) + SO 4 2− (aq) ⇌ NiSO 4 o (aq). The equilibrium constants K A for the two systems, which correspond to the formation of all types of ion pairs (solvent−solvent-separated, solvent-separated, and contact ion pairs), agree remarkably well with results calculated from solubility measurements at much higher concentrations. The results were described by the temperature-dependent equilibrium constant model to a precision of ± 0.03 in log K A .

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)0.001
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 score0.194
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.073
GPT teacher head0.243
Teacher spread0.171 · 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

Citations15
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Chemical & Engineering DataSame topicChemical and Physical Properties in Aqueous SolutionsFrench-language works237,207