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Record W4246070458 · doi:10.26434/chemrxiv.13788865.v1

The Relation Between Ejection Mechanism and Ion Abundance in the Electric Double Layer of Drops

2021· preprint· en· W4246070458 on OpenAlexafffund
Victor Kwan, Ryan O’Dwyer, David R. Laur, Styliani Consta

Bibliographic record

VenueChemRxiv · 2021
Typepreprint
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsWestern University
FundersUniversidad de Buenos AiresNatural Sciences and Engineering Research Council of CanadaMitacsUniversity of Toronto
KeywordsDrop (telecommunication)IonChemistryRayleigh scatteringPartition (number theory)Voltage dropChemical physicsSurface layerAnalytical Chemistry (journal)Atomic physicsLayer (electronics)ThermodynamicsPhysicsOpticsChromatography

Abstract

fetched live from OpenAlex

The composition of outer drop layers has been associated with distinct chemical reactivity. We use atomistic modeling to examine how the composition of the surface excess charge layer (SECL) is related to the ejection mechanisms of ions. Even though the drop disintegration is inherently a non-equilibrium process we find that the equilibrium ion distribution in SECL predicts the ions that are ejected. The escape of the ions in aqueous drops takes place from conical protrusions that are global drop deformations and their appearance is independent of the location of a single ion. Our results agree with the equilibrium partition model, which associates the mass spectrum with the distribution of analytes in the drop’s double electric layer. We present evidence that atomistic simulations of minute nano-drops cannot distinguish Rayleigh fission from the ion evaporation mechanism.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.495

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 integrity0.0000.001
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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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 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

Citations0
Published2021
Admission routes2
Has abstractyes

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