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Record W4400619630 · doi:10.1016/j.jcis.2024.07.112

Unravelling soft interfaces: Visualization of gel ridges

2024· article· en· W4400619630 on OpenAlexafffund
A‐Reum Kim, Sushanta K. Mitra, Boxin Zhao

Bibliographic record

VenueJournal of Colloid and Interface Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElastomerSelf-healing hydrogelsMaterials scienceSoft matterPolymerContact angleNanotechnologyRefractive indexChemical engineeringComposite materialColloidPolymer chemistryOptoelectronics

Abstract

fetched live from OpenAlex

HYPOTHESIS: Soft materials, particularly elastomers, are extensively studied, but investigations into purely soft gel contact systems are limited due to their complex dual phases consisting of polymer and free liquids. While Dual Wavelength-Reflection Interference Confocal Microscopy (DW-RICM) is effective for noninvasively visualizing interfaces from a bottom view, it faces challenges in gel studies due to close refractive indices of polymeric networks and free liquids. We hypothesize that modulating the refractive index of soft gels using nanoparticles (NPs) enhances the visualization of contact zone beneath the free surface, providing insights into the configuration of phase-separated free oil within gel-on-gel contact systems. EXPERIMENTS: ) NPs were introduced into the organogel to modulate refractive indices. Given the lack of prior studies on the hidden contact zone between gels, various techniques, including DW-RICM, side-view imaging, and inverted optical microscopy, were employed to observe and validate our findings. Comparative analyses were conducted with elastomer-on-rigid, elastomer-on-gel, and gel-on-rigid contact systems. FINDINGS: addition did not alter the gels' mechanical and surface properties but significantly enhanced information on gel contact deformation. This enhanced visualization technique has the potential to advance our understanding of adhesive contacts in gels, providing valuable insights into interface phenomena involving biological soft tissues and cells.

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)0.001
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 score0.054
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.294
Teacher spread0.278 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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