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Record W2965170752

Multiscale Wrinkling Patterns in Helicoidal Plywood Surfaces

2019· article· en· W2965170752 on OpenAlexaff
Alejandro D. Rey, Ziheng Wang

Bibliographic record

VenueStatPhys 27 Main Conference · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceAnchoringCurvatureLiquid crystalSurface (topology)Orientation (vector space)Composite materialGeometryOpticsPhysicsMathematicsOptoelectronics
DOInot available

Abstract

fetched live from OpenAlex

Helicoidal plywoods are an ubiquitous biological fibrous composites structure found in collagen and cellulosic materials. These cholesteric liquid crystal analogues display the Bouligand architecture which is associated with bulk and surface multifunctionalities such as sensor/actuator and structural color , as well as optimized mechanical and tribological properties.    In this presentation, motivated and guided by biological surface topographies found in insects, plants, and fish scales, we present a model of surface pattern formation for chiral surfaces and reveal the elastic mechanisms that generate simple and complex wrinkling. Introducing the liquid crystal capillary vector we are able to efficiently map the relations between surface curvature, liquid crystal anchoring, chirality  and surface tension. Scaling laws of wrinkling amplitude and wave-length as a function of anchoring and chirality are derived. In the simplest case, a fiber orientation surface gradients generate a single scale harmonic whose amplitude is proportional to anchoring and whose wave-length is set by the orientation. We show how by manipulating the material property and fiber gradient space generates targeted patterns with desirable novel properties, such as low friction surfaces.

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 score0.403
Threshold uncertainty score0.745

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 head0.009
GPT teacher head0.212
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

Citations0
Published2019
Admission routes1
Has abstractyes

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