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Record W1985183096 · doi:10.1021/ic700915z

Fast Synthesis of ZnO Nanostructures by Laser-Induced Decomposition of Zinc Acetylacetonate

2007· article· en· W1985183096 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

VenueInorganic Chemistry · 2007
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsWurtzite crystal structureNanorodZincChemistryRaman spectroscopyNanostructureNanoparticleChemical engineeringSubstrate (aquarium)IrradiationAqueous solutionNanowireHydrothermal circulationNanotechnologyLaserMaterials scienceOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

A CO2 laser (lambda = 10.6 microm) was used to heat a solution of water and alcohol saturated by Zn(AcAc)2 on a fused quartz substrate in open air. After only a few seconds of irradiation, various zinc oxide (ZnO) nanostructures including nanorods and nanowires are formed near the center of the irradiated zone, surrounded by a porous thin film of ZnO nanoparticles. The type of structures produced and their localization on the substrate can be varied by selecting adequate irradiation time and laser power ranges. The deposits have been analyzed using SEM, TEM, EDS, XRD, and Raman spectroscopy, revealing that the nanorods (aspect ratio ~6) and nanowires (aspect ratio ~94) are single-crystalline structures which grow along the c axis of wurtzite ZnO. The nanoparticles are also single-crystalline and have an average diameter of 16 nm. A qualitative model for nanostructure growth is proposed, based on previous studies of aqueous solution and hydrothermal processing.

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)0.000
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 score0.002
Threshold uncertainty score0.774

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)0.0010.000

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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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