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Record W4394852504 · doi:10.1039/d4sm00022f

Flexible hydrogels connecting adhesion and wetting

2024· article· en· W4394852504 on OpenAlexafffund
A-Reum Kim, Surjyasish Mitra, Sudip Shyam, Boxin Zhao, Sushanta K. Mitra

Bibliographic record

VenueSoft Matter · 2024
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWettingWetting transitionMaterials scienceAdhesionElasticity (physics)Soft materialsAdhesiveContact angleSelf-healing hydrogelsComposite materialMechanicsNanotechnologyPolymer chemistryPhysicsLayer (electronics)

Abstract

fetched live from OpenAlex

Raindrops falling on window-panes spread upon contact, whereas hail can cause dents or scratches on the same glass window upon contact. While the former phenomenon resembles classical wetting, the latter is dictated by contact and adhesion theories. The classical Young-Dupre law applies to the wetting of pure liquids on rigid solids, whereas conventional contact mechanics theories account for rigid-on-soft or soft-on-rigid contacts with small deformations in the elastic limit. However, the crossover between adhesion and wetting is yet to be fully resolved. The key lies in the study of soft-on-soft interactions with material properties intermediate between liquids and solids. In this work, we translate adhesion to wetting by experimentally probing the static signature of hydrogels in contact with soft PDMS of varying elasticity of both the components. Consequently, we probe this transition across six orders of magnitude in terms of the characteristic elasto-adhesive parameter of the system. In doing so, we reveal previously unknown phenomenology and a theoretical model which smoothly bridges adhesion of glass spheres with total wetting of pure liquids on any given substrate.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.230
Teacher spread0.222 · 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 designNot applicable
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

Citations11
Published2024
Admission routes2
Has abstractyes

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