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Record W2257184309 · doi:10.1038/ncomms8429

Photogated humidity-driven motility

2015· article· en· W2257184309 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNature Communications · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsnot available
FundersKumoh National Institute of TechnologyYork UniversityNew York University Abu Dhabi
KeywordsHumidityMotilityBiologyCell biologyMeteorologyPhysics

Abstract

fetched live from OpenAlex

Hygroinduced motion is a fundamental process of energy conversion that is essential for applications that require contactless actuation in response to the day-night rhythm of atmospheric humidity. Here we demonstrate that mechanical bistability caused by rapid and anisotropic adsorption and desorption of water vapour by a flexible dynamic element that harnesses the chemical potential across very small humidity gradients for perpetual motion can be effectively modulated with light. A mechanically robust material capable of rapid exchange of water with the surroundings is prepared that undergoes swift locomotion in effect to periodic shape reconfiguration with turnover frequency of <150 min(-1). The element can lift objects ∼85 times heavier and can transport cargos ∼20 times heavier than itself. Having an azobenzene-containing conjugate as a photoactive dopant, this entirely humidity-driven self-actuation can be controlled remotely with ultraviolet light, thus setting a platform for next-generation smart biomimetic hybrids.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.317

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 head0.040
GPT teacher head0.295
Teacher spread0.255 · 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