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Highly-stable silver nanobelts joined via diffusion-free attachment

2016· article· en· W2417501367 on OpenAlexafffund
Geoffrey Rivers, Ehsan Marzbanrad, Michael David Hook, Pearl Lee‐Sullivan, Y. Zhou, Boxin Zhao

Bibliographic record

VenueNanotechnology · 2016
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsMaterials scienceDiffusionNanowireNanotechnologyNanoparticleParticle (ecology)Silver nanoparticleSurface diffusionChemical engineeringPhysical chemistry

Abstract

fetched live from OpenAlex

Silver nanobelts are demonstrated here to undergo inter-particle joining at relatively low temperatures of less than 180 °C. For surface-coated networks of nanobelts this joining reduced the network sheet resistance by 95%. The joining mechanism appears to be non-diffusional oriented attachment, caused by the thermal reactivation of the halted oriented attachment mechanism that occurred originally at room temperature during the rapid nanobelt synthesis. This self-assembly mechanism was explored by in situ electrical and calorimetric experiments, and supported by electron microscopy. Unlike pentagonal silver nanowires, silver nanobelts do not rely on diffusional instability to achieve workably low joining temperatures. The oriented attachment displayed by nanobelts represents a new approach to achieving valuable reductions in network resistance, disentangled from the instability and diffusion-driven failure by nanoparticle degradation displayed by competing silver nanoparticles.

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 score0.078
Threshold uncertainty score0.799

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 science0.0010.001
Research integrity0.0010.000
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 head0.199
Teacher spread0.192 · 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

Citations4
Published2016
Admission routes2
Has abstractyes

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