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Record W2618517665 · doi:10.1021/acs.jpclett.7b01005

pH-Dependent Inversion of Hofmeister Trends in the Water Structure of the Electrical Double Layer

2017· article· en· W2618517665 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Alberta
FundersCanadian Centre for Clean Coal/Carbon and Mineral Processing TechnologiesNatural Sciences and Engineering Research Council of CanadaAlfred P. Sloan FoundationUniversity of AlbertaGovernment of CanadaCanada Foundation for InnovationSuncor Energy Incorporated
KeywordsInversion (geology)Hofmeister seriesLayer (electronics)ChemistryChemical physicsGeophysicsMaterials scienceGeologyNanotechnologyIonGeomorphologyOrganic chemistry

Abstract

fetched live from OpenAlex

Specific ion effects (SIEs) are known to influence the acid/base behavior of silica and the interfacial structure of water, yet evidence of the effect of pH on SIEs is lacking. Here broadband vibrational sum frequency generation (SFG) spectroscopy was used to study SIEs on the water structure at the electrical double layer (EDL) of silica as a function of pH and monovalent cation identity from pH 2–12 at 0.5 M salt concentration. SFG results indicate a direct Hofmeister series of cation adsorption at pH 8 (Li + < Na + < K + < Cs + ), with an inversion in this series occurring at pH > 10. In addition, an inversion in SFG intensity trends also occurred at pH < 6, which was attributed to contributions from asymmetric cation hydration and EDL overcharging. The highly pH-dependent SIEs for silica/water have implications for EDL models that often assume pH-independent parameters.

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.

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 score0.006
Threshold uncertainty score0.214

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 science0.0010.000
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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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