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Record W4206290996 · doi:10.1039/d1na00872b

Metal nanowires grown <i>in situ</i> on polymeric fibres for electronic textiles

2022· article· en· W4206290996 on OpenAlexfundno aff
Oindrila Halder, Muriel E. Layani-Tzadka, Shiran Ziv Sharabani, Gil Markovich, Amit Sitt

Bibliographic record

VenueNanoscale Advances · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsnot available
FundersResearch, Development and Engineering CommandArmy Research OfficeMinistry of Science and Technology, IsraelAzrieli FoundationTel Aviv University
KeywordsNanowireMaterials scienceMetalIn situNanotechnologyComposite materialPolymer scienceMetallurgyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

-glycolic) acid and nylon microfibres, we show that the NW network morphology depends on the diameter of the polymer fibres, where at small diameters (1-2 μm), the NWs form a randomly oriented network, but for diameters above several micrometers, the NWs wrap around the fibres transversally. This phenomenon is associated with the stiffness of the surfactant templates used for the NW formation. The NW-decorated fibres exhibit a significant increase in conductivity. Moreover, single fibres can be stretched up to ∼15% before losing the electrical conductivity, while non-woven meshes could be stretched by about 25% before losing the conductivity. We believe that the approach demonstrated here can be extended to other polymeric fibres and that these flexible and transparent metal-coated polymer fibres could be useful for various smart electronic textile applications.

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 score0.363
Threshold uncertainty score0.858

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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