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Record W2783135855 · doi:10.1021/acs.jpclett.7b03003

Capillary Condensation in 8 nm Deep Channels

2018· article· en· W2783135855 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 · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsUniversity of Toronto
FundersAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCondensationBridging (networking)Chemical physicsNanoscopic scaleCapillary condensationMaterials scienceNanotechnologyCapillary actionThermodynamicsChemistryPhysicsPhysical chemistryComputer science

Abstract

fetched live from OpenAlex

Condensation on the nanoscale is essential to understand many natural and synthetic systems relevant to water, air, and energy. Despite its importance, the underlying physics of condensation initiation and propagation remain largely unknown at sub-10 nm, mainly due to the challenges of controlling and probing such small systems. Here we study the condensation of n-propane down to 8 nm confinement in a nanofluidic system, distinct from previous studies at ∼100 nm. The condensation initiates significantly earlier in the 8 nm channels, and it initiates from the entrance, in contrast to channels just 10 times larger. The condensate propagation is observed to be governed by two liquid-vapor interfaces with an interplay between film and bridging effects. We model the experimental results using classical theories and find good agreement, demonstrating that this 8 nm nonpolar fluid system can be treated as a continuum from a thermodynamic perspective, despite having only 10-20 molecular layers.

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 score0.079
Threshold uncertainty score0.696

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 integrity0.0000.000
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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