MétaCan
Menu
Back to cohort

Hydrothermal Growth of Vertical ZnO Nanorods

2009· article· en· W1997858092 on OpenAlexaff
Yiling Lee, Yu Zhang, Serene Lay Geok Ng, Fransiska Cecilia Kartawidjaja, John Wang

Bibliographic record

VenueJournal of the American Ceramic Society · 2009
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsAdvanced Micro Devices (Canada)
FundersNational University of Singapore
KeywordsNanorodMaterials scienceWurtzite crystal structureEpitaxyNucleationSeedingHydrothermal circulationChemical engineeringLayer (electronics)NanotechnologySurface roughnessComposite materialZincChemistryMetallurgy

Abstract

fetched live from OpenAlex

Vertically aligned, single crystalline ZnO nanorods with a high packing density and diameter of ∼60 nm have been successfully synthesized via a low‐temperature hydrothermal route on glass substrates pre‐deposited with a ZnO seeding layer. The seeding layer exhibits an epitaxial effect on the growth and alignment of the ZnO nanorods. This epitaxial effect can arise from two considerations, namely the crystalline orientation and surface roughness of the seeding layer, which can be controlled by the curing temperature. The ZnO seeding layer that was cured at 350°C exhibited a preferred (0002) crystalline orientation of wurtzite hexagonal structure and a low surface roughness. It was demonstrated to promote the vertical growth of ZnO nanorods. The ZnO nanorods grew in an almost linear relationship with hydrothermal time up to 8 h, but thereafter started to dissolve as the reaction time extended beyond 8 h, due to competition from the homogeneous nucleation of ZnO microparticles in the solution.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.246
Teacher spread0.235 · 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

Citations44
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Ceramic SocietySame topicZnO doping and propertiesFrench-language works237,207