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Record W6920562602 · doi:10.60692/rdkge-3ea71

Self-assembly of silicon nanowires studied by advanced transmission electron microscopy

2017· article· en· W6920562602 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2017
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsTekna Plasma Systems (Canada)Institut National de la Recherche Scientifique
Fundersnot available
KeywordsTransmission electron microscopySilicon nanowiresSiliconScanning transmission electron microscopyNanowireNanostructureElectron tomographyEnergy filtered transmission electron microscopyNanoparticle

Abstract

fetched live from OpenAlex

Scanning transmission electron microscopy (STEM) was successfully applied to the analysis of silicon nanowires (SiNWs) that were self-assembled during an inductively coupled plasma (ICP) process. The ICP-synthesized SiNWs were found to present a Si-SiO2 core-shell structure and length varying from ≈100 nm to 2-3 μm. The shorter SiNWs (maximum length ≈300 nm) were generally found to possess a nanoparticle at their tip. STEM energy dispersive X-ray (EDX) spectroscopy combined with electron tomography performed on these nanostructures revealed that they contain iron, clearly demonstrating that the short ICP-synthesized SiNWs grew via an iron-catalyzed vapor-liquid-solid (VLS) mechanism within the plasma reactor. Both the STEM tomography and STEM-EDX analysis contributed to gain further insight into the self-assembly process. In the long-term, this approach might be used to optimize the synthesis of VLS-grown SiNWs via ICP as a competitive technique to the well-established bottom-up approaches used for the production of thin SiNWs.

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 score0.263
Threshold uncertainty score0.559

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 communication0.0000.001
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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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