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Record W2323128653 · doi:10.1021/jp3081832

Tetraoctylphosphonium Tetrakis(pentafluorophenyl)borate Room Temperature Ionic Liquid toward Enhanced Physicochemical Properties for Electrochemistry

2012· article· en· W2323128653 on OpenAlexaff
Zhifeng Ding

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2012
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsIonic liquidElectrochemical windowElectrochemistryChemistryElectrolyteCyclic voltammetryVoltammetryInorganic chemistryITIESMetalKineticsElectrodeAnalytical Chemistry (journal)Physical chemistryIonic conductivityOrganic chemistry

Abstract

fetched live from OpenAlex

Presented herein is the facile preparation of a new room temperature ionic liquid (RTIL), tetraoctylphosphonium tetrakis(pentafluorophenyl)borate (P(8888)TB). Subsequently, its physicochemical properties such as density, viscosity, and conductivity were characterized relative to temperature, demonstrating values of 1.22 g·cm(-3), 727 mPa·s, and 180 μS·cm(-1), respectively, at 60 °C. The electrochemistry of P(8888)TB was also investigated using cyclic voltammetry at a Pt-disk ultramicroelectrode and at a microinterface between water and the RTIL; this analysis revealed a wide metal-electrolyte potential window, ∼3.5 V, and a large liquid|liquid polarizable potential window, ∼0.9 V, at a temperature of 60 °C. Additionally, electron transfer (ET) reactions at a metal electrode|RTIL interface along with ion transfer (IT) reactions at the water|P(8888)TB interface were examined; the kinetics of these reactions were explored using finite element analysis. Increased ET and IT kinetics combined with enhancements of physicochemical properties versus RTILs we made previously seemingly suggest modest improvements. However, taken as a whole, they demonstrate significant progress toward a hydrophobic RTIL that can be used in conventional electrochemistry and biphasic metal ion extractions.

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 categoriesMeta-epidemiology (narrow)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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.

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

Citations24
Published2012
Admission routes1
Has abstractyes

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