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Record W2897853864 · doi:10.1088/2058-8585/aae8c0

Stretchable metal films

2018· article· en· W2897853864 on OpenAlexafffund
Sara S. Mechael, Yunyun Wu, Kory Schlingman, Tricia Breen Carmichael

Bibliographic record

VenueFlexible and Printed Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStretchable electronicsInterfacingElectronicsMaterials scienceWearable technologyElectrical conductorBendingNanotechnologyWearable computerMechanical engineeringEngineering physicsElectrical engineeringComposite materialComputer scienceEngineeringEmbedded system

Abstract

fetched live from OpenAlex

Abstract The current growth of the wearable electronics market has inspired the development of soft and stretchable interfacing between electronics and the human body. Stretchable conductors are critical to the evolution of stretchable and wearable electronics. In this topical review, we discuss notable contributions to the field of stretchable metal films. Although the high conductivity of metals is an asset in electronic devices, their mechanical properties are not readily compatible with stretchable devices. We discuss the two main approaches to preserve conductivity during strain: conversion of stretching to bending strain and using topography to control cracking. These approaches lead to two contrasting electrical responses to mechanical deformation, and we discuss the application of these responses in devices as interconnects and sensors.

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 score0.006
Threshold uncertainty score0.019

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)0.0060.001

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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

Citations22
Published2018
Admission routes2
Has abstractyes

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