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Record W4415474051 · doi:10.1063/5.0281822

Vapor-phase growth of single-crystal defect-free nanowires: Interface dynamics, morphology control, and emerging applications

2025· article· en· W4415474051 on OpenAlexafffund
Yushun Liu, Guo‐zhen Zhu

Bibliographic record

VenueChemical Physics Reviews · 2025
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsNanowireNucleationOxideInterface (matter)Substrate (aquarium)Vapor–liquid–solid method

Abstract

fetched live from OpenAlex

Nanowire-based technologies in electronics, photonics, and sensing demand high-quality nanowires with precise control over structure, morphology, and composition. Vapor-phase growth, such as vapor–liquid–solid and vapor–solid–solid, has enabled the controlled synthesis of elemental, group III–V, group II–VI, and a few oxide nanowires; however, many challenges remain. This review highlights the interface dynamics at the seed by comparing conventional growth with an unconventional set-up that has demonstrated success in controllably synthesizing single-crystal, defect-free oxide nanowires. Dynamic aspects are amplified when the substrate itself thermally evaporates at elevated temperatures to generate vapor species that are subsequently encapsulated on gold seeds, enabling nanowire growth at rates of ∼200 nm/min. This review examines the structural characteristics of gold–oxide interfaces, given their critical role in mediating key growth steps, ranging from oxide mass transport across vapors to solid phases, to nucleation and lateral growth at the nanowire growth front. Examples demonstrating how control over interface dynamics can tune nanowire morphology and functionality are presented. We anticipate that this review will provide an alternative perspective on addressing some fundamental processes in vapor-phase nanowire growth and provide valuable insights for further expansion of nanowire synthesis to new materials systems and 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: none
Teacher disagreement score0.919
Threshold uncertainty score0.723

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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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
Published2025
Admission routes2
Has abstractyes

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