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Record W4411472826 · doi:10.1021/acs.langmuir.5c02127

Intensity-Calibrated Variable-Angle Surface Spectroscopy Provides the Electrostatic Potential at the Interface between Bonded and Diffuse Regions of the Electrical Double Layer

2025· article· en· W4411472826 on OpenAlexafffund
Md. Mosfeq Uddin, Dennis K. Hore

Bibliographic record

VenueLangmuir · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpectroscopyChemistryIntensity (physics)SlippingSilanolMolecular physicsIonic bondingChemical physicsMeasure (data warehouse)Plane (geometry)Analytical Chemistry (journal)OpticsPhysicsGeometryIon

Abstract

fetched live from OpenAlex

Second-order nonlinear optical spectroscopy is capable of separating contributions of water molecules bonded to a charged surface from those in the diffuse portion of the electrical double layer on account of the phase-matching considerations that dictate how signals are accumulated over a finite distance. One of the most characteristic features of this interfacial water structure is the electrical potential at the distance from the surface that separates these two regions. Here we describe a scheme for calibrating the absolute second-order susceptibility of the silica-aqueous interface and thereby provide the first account of intensity-based on-resonance sum-frequency generation to measure the potential at the interface between the bonded and diffuse water structures at low ionic strength. Our finding that the magnitude of the potential is slightly greater than the ζ-potential suggests that the structural influence of the surface silanol groups does not extend quite to the slipping plane.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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