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Record W3201646394 · doi:10.1021/acsami.1c12544

Spectroelectrochemical Detection of Water Dissociation in Bipolar Membranes

2021· article· en· W3201646394 on OpenAlexafffund
Amelia Hohenadel, Apurva Shantilal Gangrade, Steven Holdcroft

Bibliographic record

VenueACS Applied Materials & Interfaces · 2021
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaBritish Columbia Innovation Council
KeywordsDissociation (chemistry)MembraneIonMaterials scienceLimiting currentAnalytical Chemistry (journal)ElectrochemistryIon exchangeSelf-ionization of waterWater splittingChemical physicsElectrodeChemistryPhysical chemistryChromatographyCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

The potentials at which water dissociation occurs in bipolar membranes (BPM) and the relationship between water dissociation and current–voltage curve characteristics are explored using a novel spectroelectrochemical approach in which an anion exchange membrane is doped with a pH indicator. Using this method, we visually detect a pH change in the BPM resulting from OH– formed during the water dissociation reaction. The color change is measured with a UV/vis spectrometer, while electrochemical characterization of the BPM is performed simultaneously. Additional measurements were performed on BPMs with varying anion and cation exchange membrane layer thickness. Our measurements provide direct evidence of water dissociation occurring within a BPM at cross-membrane potentials below 0.5 V, within the first limiting current density region. We also show that the effects of changing bulk anion and cation exchange layer thickness is highly dependent on the permselectivity of these layers.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.572

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 science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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

Citations16
Published2021
Admission routes2
Has abstractyes

Explore more

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