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Record W2148581200 · doi:10.1002/smll.201101596

Green Nanochemistry: Metal Oxide Nanoparticles and Porous Thin Films from Bare Metal Powders

2011· article· en· W2148581200 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSmall · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCopper-based nanomaterials and applications
Canadian institutionsUniversity of Toronto
FundersBilkent ÜniversitesiNatural Sciences and Engineering Research Council of CanadaTürkiye Bilimler Akademisi
KeywordsNanochemistryMaterials scienceNanoporousOxideNanotechnologyDissolutionMetalAqueous solutionNanoparticleMicrometerPorosityChemical engineeringNoble metalMetallurgyOrganic chemistryComposite materialChemistryOptics

Abstract

fetched live from OpenAlex

A universal, simple, robust, widely applicable and cost-effective aqueous process is described for a controlled oxidative dissolution process of micrometer-sized metal powders to form high-purity aqueous dispersions of colloidally stable 3-8 nm metal oxide nanoparticles. Their utilization for making single and multilayer optically transparent high-surface-area nanoporous films is demonstrated. This facile synthesis is anticipated to find numerous applications in materials science, engineering, and nanomedicine.

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 categoriesInsufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score0.999

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)0.0020.000

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 head0.030
GPT teacher head0.217
Teacher spread0.187 · 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