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Record W2107756553 · doi:10.1002/chem.200700448

Controlled Growth of SnO<sub>2</sub> Hierarchical Nanostructures by a Multistep Thermal Vapor Deposition Process

2007· article· en· W2107756553 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemistry - A European Journal · 2007
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsNanostructureMaterials scienceNanowireChemical vapor depositionNanotechnologyHeterojunctionDeposition (geology)ThermalChemical engineeringOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Branched and sub-branched SnO(2) hierarchical architectures in which numerous aligned nanowires grew on the surface of nanobelt substrates have been obtained by a multistep thermal vapor deposition route. Branch size and morphology can be controlled by adjusting the temperature and duration of growth. The same approach was used to grow branched ZnO-SnO(2) heterojunction nanostructures. In addition, the third level of SnO(2) nanostructures was obtained by repeating the vapor deposition growth process. This technique provides a general, facile, and convenient approach for preparing even more complex nanoarchitectures, and should open up new opportunities for both fundamental research and applications, such as nanobelt-based three-dimensional nanodevices.

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.

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)0.001
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 score0.003
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.214
Teacher spread0.207 · 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