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Record W2015168238 · doi:10.1039/c4cp05383d

Variabilities and uncertainties in characterising water transport kinetics in glassy and ultraviscous aerosol

2015· article· en· W2015168238 on OpenAlexaff
Andrew M. J. Rickards, Young-Chul Song, Rachael E. H. Miles, Thomas C. Preston, Jonathan P. Reid

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2015
Typearticle
Languageen
FieldMaterials Science
TopicGlass properties and applications
Canadian institutionsMcGill University
FundersEngineering and Physical Sciences Research CouncilNatural Environment Research CouncilSight Research UK
KeywordsAerosolKineticsEnvironmental scienceMeteorologyAtmospheric sciencesThermodynamicsStatistical physicsGeologyPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

We present a comprehensive evaluation of the variabilities and uncertainties present in determining the kinetics of water transport in ultraviscous aerosol droplets, alongside new measurements of the water transport timescale in sucrose aerosol. Measurements are performed on individual droplets captured using aerosol optical tweezers and the change in particle size during water evaporation or condensation is inferred from shifts in the wavelength of the whispering gallery mode peaks at which spontaneous Raman scattering is enhanced. The characteristic relaxation timescale (τ) for condensation or evaporation of water from viscous droplets following a change in gas phase relative humidity can be described by the Kohlrausch-Williams-Watts function. To adequately characterise the water transport kinetics and determine τ, sufficient time must be allowed for the particle to progress towards the final state. However, instabilities in the environmental conditions can prevent an accurate characterisation of the kinetics over such long time frames. Comparison with established thermodynamic and diffusional water transport models suggests the determination of τ is insensitive to the choice of thermodynamic treatment. We report excellent agreement between experimental and simulated evaporation timescales, and investigate the scaling of τ with droplet radius. A clear increase in τ is observed for condensation with increase in drying (wait) time. This trend is qualitatively supported by model simulations.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.229
Teacher spread0.211 · 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

Citations45
Published2015
Admission routes1
Has abstractyes

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