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Si-NWs

2014· book-chapter· en· W2484881889 on OpenAlexaff
Maha M. Khayyat, Brahim Aïssa

Bibliographic record

VenueAdvances in chemical and materials engineering book series · 2014
Typebook-chapter
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMPB Technologies & Communications (Canada)
Fundersnot available
KeywordsNanotechnologyNanowireNanomaterialsMaterials scienceSilicon nanowires

Abstract

fetched live from OpenAlex

Surfaces and interfaces have a special significance to nanotechnology because the surface/volume ratio of nanomaterials is larger than for the bulk ones. Therefore, interfaces of nanomaterials are more important to the properties of the nanomaterials than for larger scale materials. Moreover, crystal growth and more particularly Nanowires (NWs) growth occurs at the interfaces between the growing crystals and the supply media. This chapter focuses on the silicon nanowires grown using a Vapor-Liquid-Solid (VLS) concept. One of the key advantages of VLS is that controlled placement or templating of the seed metal produces templated NW growth. This templating is required for integration of NWs with other devices, which is desirable for many applications. The authors discuss issues on the discovery of fundamentally new phenomena versus performance benchmarking for many of the Si-NW applications. Finally, the authors attempt to look into the future and offer their personal opinions on the upcoming trends in nanowire research.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.000

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0470.025

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 head0.003
GPT teacher head0.174
Teacher spread0.171 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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