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Record W4293703324 · doi:10.1021/jacs.2c01830

Water Structure in the Electrical Double Layer and the Contributions to the Total Interfacial Potential at Different Surface Charge Densities

2022· article· en· W4293703324 on OpenAlexafffund
Benjamin Rehl, Emily Ma, Shyam Parshotam, Emma L. DeWalt-Kerian, Tianli Liu, Franz M. Geiger, Julianne M. Gibbs

Bibliographic record

VenueJournal of the American Chemical Society · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Alberta
FundersAir Force Office of Scientific ResearchGovernment of OntarioNatural Sciences and Engineering Research Council of CanadaNorthwestern UniversityAlfred P. Sloan Foundation
KeywordsChemistryCharge (physics)Surface (topology)Layer (electronics)Chemical physicsCharge densitySurface chargeSurface layerPhysical chemistryOrganic chemistryGeometryQuantum mechanics

Abstract

fetched live from OpenAlex

The electric double layer governs the processes of all charged surfaces in aqueous solutions; however, elucidating the structure of the water molecules is challenging for even the most advanced spectroscopic techniques. Here, we present the individual Stern layer and diffuse layer OH stretching spectra at the silica/water interface in the presence of NaCl over a wide pH range using a combination of vibrational sum frequency generation spectroscopy, heterodyned second harmonic generation, and streaming potential measurements. We find that the Stern layer water molecules and diffuse layer water molecules respond differently to pH changes: unlike the diffuse layer, whose water molecules remain net-oriented in one direction, water molecules in the Stern layer flip their net orientation as the solution pH is reduced from basic to acidic. We obtain an experimental estimate of the non-Gouy-Chapman (Stern) potential contribution to the total potential drop across the insulator/electrolyte interface and discuss it in the context of dipolar, quadrupolar, and higher order potential contributions that vary with the observed changes in the net orientation of water in the Stern layer. Our findings show that a purely Gouy-Chapman (Stern) view is insufficient to accurately describe the electrical double layer of aqueous interfaces.

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 score0.029
Threshold uncertainty score0.522

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.005
GPT teacher head0.243
Teacher spread0.238 · 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

Citations117
Published2022
Admission routes2
Has abstractyes

Explore more

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