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Record W3005116031 · doi:10.1098/rsta.2019.0445

4D pine scale: biomimetic 4D printed autonomous scale and flap structures capable of multi-phase movement

2020· article· en· W3005116031 on OpenAlexaff
David Correa, Simon Poppinga, Max D. Mylo, Anna S. Westermeier, Bernd Bruchmann, Achim Menges, Thomas Speck

Bibliographic record

VenuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversity of Waterloo
FundersJoint Research Network on Advanced Materials and SystemsDeutsche Forschungsgemeinschaft
KeywordsBiomimeticsScale (ratio)Materials scienceBendingSoft roboticsComposite materialNanotechnologyComputer scienceArtificial intelligenceRobotPhysics

Abstract

fetched live from OpenAlex

) cone seed scales. The synthetic kinematic response is made possible through novel four-dimensional (4D) printing techniques with anisotropic material use, namely copolymers with embedded cellulose fibrils and ABS polymer. Multi-phase motion like the subsequent transversal and longitudinal bending deformation during desiccation of a natural pinecone scale can be structurally programmed into such printed hygromorphs. Both the natural concept generator (Bhutan pinecone scale) and the biomimetic technical structure (4D printed scale) were comparatively investigated as to their displacement and strain over time via three-dimensional digital image correlation methods. Our bioinspired prototypes can be the basis for tailored autonomous and self-sufficient flap and scale structures performing complex consecutive motions for technical applications, e.g. in architecture and soft robotics. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology (part 3)'.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.018
GPT teacher head0.240
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 source (direct Gemma or distilled Codex), 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

Citations118
Published2020
Admission routes1
Has abstractyes

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Same venuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesSame topicAdvanced Materials and MechanicsFrench-language works237,207