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Record W2574951338 · doi:10.22059/jcamech.2016.59260

Sessile and Pendant Micro-Liter Drops Evaporate at Different Rates: An Experimental Approach

2016· article· en· W2574951338 on OpenAlexaff
M. D. Moore, Alidad Amirfazli, Seyed Farshid Chini

Bibliographic record

VenueApplied and Computational Mechanics · 2016
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsYork UniversityUniversity of Alberta
Fundersnot available
KeywordsSessile drop techniqueDrop (telecommunication)BuoyancyEvaporationContact angleSolid surfaceChemistryMaterials scienceAnalytical Chemistry (journal)Composite materialMechanicsThermodynamicsChromatographyChemical physics

Abstract

fetched live from OpenAlex

Evaporation of micro-liter drops from solid surfaces at room condition is mainly governed by diffusion. Therefore, there should be no difference between evaporation rate of sessile and pendant drops. However, some studies indicate a difference and explain the difference using buoyancy. The objective here is to reconcile the inconsistency in the literature. For that, first, by comparing two identical suspended drops, one with a plate on top and the other underneath with a space between drop and plate, we showed the contribution of buoyancy in evaporation is at most less than 8%. When a plate was placed on top, water (its vapor is lighter than air) evaporated slower and hydrocarbons (their vapors are heavier than air) evaporated faster. Interestingly, it was observed when drops touch the plates (i.e. sessile and pendant drops), both water and hydrocarbon drops evaporated faster in sessile configuration. The observation for hydrocarbons is in contradiction with what buoyancy explains. To describe the difference, different scenarios were studied. It was found that sessile drops stay longer in the “constant wetted area” (CWA) mode, before switching to the CCA (constant contact angle) mode, e.g. a 4 µl sessile water drop on a Poly(methyl methacrylate) coated silicon stays in the CWA mode for 318 s whereas for a similar pendant drop this time is 274 s. Considering the fact that evaporation rate in the CWA mode is 30–40% higher compared to the CCA mode, the faster evaporation rate of sessile drops may be explained.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.390

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)0.0000.000

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 head0.013
GPT teacher head0.217
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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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