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Record W2552968757 · doi:10.1021/acs.jpca.6b11241

Models of Isotopic Water Diffusion in Spherical Aerosol Particles

2016· article· en· W2552968757 on OpenAlexafffund
Ali Moridnejad, Thomas C. Preston

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDiffusionChemistryParticle (ecology)AerosolBoundary value problemThermodynamicsDesorptionAqueous solutionViscositySorptionAdsorptionPhysical chemistryPhysics

Abstract

fetched live from OpenAlex

Isotopic exchange experiments that utilize D 2 O and H 2 O have received attention as a method for studying water diffusion in high viscosity aerosol particles. However, the mathematical models used to retrieve diffusion coefficients from these measurements have yet to be critically examined. Here, two models for the isotopic exchange of D 2 O and H 2 O in spherical particles are analyzed and compared. The primary difference between the two models is the choice of boundary condition at the surface of the spherical particle. In one model, it is assumed that the concentration of D 2 O at the surface is fixed, while in the other model, it is assumed that, at the particle surface, the concentration of D 2 O in the condensed phase is in equilibrium with D 2 O vapor. Closed-form expressions for the two boundary value problems that describe these physical models are found and discussed. Then, specific examples of aqueous droplets containing either sucrose, citric acid, and shikimic acid are examined with both models. It is found that at low relative humidities the choice of boundary condition has a negligible effect on the predicted lifetime of isotopic exchange, while at high relative humidities predicted lifetimes can differ by orders of magnitude. The implication of this result is that the choice of model can greatly affect diffusion coefficients retrieved from experimental measurements under certain conditions. Finally, discrepancies between diffusion coefficients measured using isotopic exchange and water sorption and desorption experiments are discussed.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
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 head0.012
GPT teacher head0.203
Teacher spread0.191 · 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

Citations13
Published2016
Admission routes2
Has abstractyes

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