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Record W4298140682 · doi:10.1149/10914.0011ecst

The Transition (vs ΔpK<sub>a</sub>) from Triple Ions to Free Cations in Poor Protic Ionic Liquids Made from Weak Acids

2022· article· en· W4298140682 on OpenAlexaff
Smit S. Rana, Allan L. L. East

Bibliographic record

VenueECS Transactions · 2022
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsChemistryIonCationic polymerizationIonizationIonic bondingAmine gas treatingIonic liquidStoichiometryInorganic chemistryBase (topology)ConductivityGibbs free energyCarboxylatePhysical chemistryComputational chemistryThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

In mixtures of amines with carboxylic acids, the limited ionicity at 1:1 stoichiometric mixtures is due to insufficient ionization or ion pairing in low-dielectric environments. Higher conductivities have historically been seen at roughly 4:1 acid/base mixing ratios, where simulations have revealed large (and thus more stable) ions: homoassociated anions (AH)(AH)(A−)(HA)(HA) and cationic triple ions (BH+)(AH)(A−)(HA)(HB+). Recent work in understanding the Gibbs energies for degree-of-ionization equilibria hints that there may be an onset, for systems with an acid-base pKa difference increasing towards 10, for the formation of free (unpaired) protonate-amine cations BH+. The transition with increasing ΔpKa is explored in this work, to aid in the prediction of ionicity and conductivity of protic ionic liquids.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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