MétaCan
Menu
Back to cohort
Record W4402827540 · doi:10.3390/polym16192710

Highly Stretchable Composite Conductive Fibers (SCCFs) and Their Applications

2024· review· en· W4402827540 on OpenAlexaff
Diane Tang, Ruixiang Qu, Huacui Xiang, Enjian He, Han-Shi Hu, Zhijun Ma, Guojun Liu, Yen Wei, Jiujiang Ji

Bibliographic record

VenuePolymers · 2024
Typereview
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsQueen's University
FundersNatural Science Foundation of Beijing Municipality
KeywordsElectrical conductorMaterials scienceBioelectronicsNanotechnologyElectronicsWearable technologyWearable computerElectrically conductiveConductive polymerComposite numberBiocompatibilityComputer scienceComposite materialPolymerElectrical engineeringEngineeringBiosensor

Abstract

fetched live from OpenAlex

Stretchable composite conductive fibers (SCCFs) exhibit remarkable conductivity, stretchability, breathability, and biocompatibility, making them ideal candidates for wearable electronics and bioelectronics. The exploitation of SCCFs in electronic devices requires a careful balance of many aspects, including material selection and process methodologies, to address the complex challenges associated with their electrical and mechanical properties. In this review, we elucidate the conductive mechanism of SCCFs and summarize strategies for integrating various conductors with stretchable fibers, emphasizing the primary challenges in fabricating highly conductive fibers. Furthermore, we explore the multifaceted applications of SCCFs-based frameworks in wearable electronic devices. This review aims to emphasize the significance of SCCFs and offers insights into their conductive mechanisms, material selection, manufacturing technologies, and performance improvement. Hopefully, it can guide the innovative development of SCCFs and broaden their application potential.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.273
Teacher spread0.247 · 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
GenreReview

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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePolymersSame topicAdvanced Sensor and Energy Harvesting MaterialsFrench-language works237,207