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Record W2324040199 · doi:10.1021/jp308313v

Collective Proton Dynamics at Highly Charged Interfaces Studied by Ab Initio Metadynamics

2012· article· en· W2324040199 on OpenAlexafffund
Swati Vartak, Ata Roudgar, Anatoly Golovnev, Michael Eikerling

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2012
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
FundersDivision of Materials ResearchNatural Sciences and Engineering Research Council of CanadaWestern Canada Research Grid
KeywordsChemical physicsMetadynamicsProtonHydrogen bondHydroniumAb initioChemistryAb initio quantum chemistry methodsDelocalized electronMolecular dynamicsComputational chemistryMaterials scienceIonPhysical chemistryMoleculeOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Surface proton conduction is of utmost importance in biology, materials science, and electrochemistry; yet experimental findings of ultrafast proton transport at densely packed arrays of anionic surface groups have remained controversial and unexplained. We present an ab initio molecular dynamics study of proton dynamics at sulfonic-acid terminated surface groups. Results furnish a highly efficient collective mechanism of hydronium ion translocations at a critical surface group separation of ~6.5 Å. Orientational fluctuations of SG trigger hydrogen bond breaking that sets off the hydronium ion motion. The activation free energy of this process is 0.3 eV (±0.1 eV). The soliton-like nature of this mechanism is owed to the trigonal symmetry of sulfonate anions and exceptionally strong interfacial hydrogen bonding. These insights should stimulate surface conductance studies at SG monolayers with sulfonic acid groups, and they bolster efforts in designing proton conducting polymers conducive to fuel cell operation above ~100 °C.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.205
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations19
Published2012
Admission routes2
Has abstractyes

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