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Record W1999713799 · doi:10.1021/am5087177

Printing Small Dots from Large Drops

2015· article· en· W1999713799 on OpenAlexaff
Emma L. Talbot, Huai Nyin Yow, Lisong Yang, Arganthaël Berson, Simon Biggs, Colin D. Bain

Bibliographic record

VenueACS Applied Materials & Interfaces · 2015
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsInstitute of Particle Physics
FundersEngineering and Physical Sciences Research Council
KeywordsMaterials scienceNanotechnologyQuantum dotEngineering physics

Abstract

fetched live from OpenAlex

Printing of droplets of pure solvents containing suspended solids typically leads to a ring stain due to convective transport of the particles toward the contact line during evaporation of the solvent. In mixtures of volatile solvents, recirculating cells driven by surface tension gradients are established that lead to migration of colloidal particles toward the center of the droplet. In favorable cases, a dense disk of particles forms with a diameter much smaller than that of the droplet. In the latter stages of drying, convective transport of the particles radially toward the contact line still occurs. Two strategies are described to fix the distribution of particles in a compact disk much smaller than the initial diameter of the drying droplet. First, a nanoparticulate clay is added to induce an evaporation-driven sol-gel transition that inhibits convective flow during the latter stages of drying. Second, a nonadsorbing polymer is added to induce depletion flocculation that restricts particle motion after the particles have been concentrated near the center of the droplet. The area of the resulting deposit can be as little as 10% of the footprint of the printed droplet.

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 categoriesMeta-epidemiology (narrow)
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 score0.005
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.023
GPT teacher head0.208
Teacher spread0.185 · 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.

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

Citations40
Published2015
Admission routes1
Has abstractyes

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