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Record W2282754025 · doi:10.1504/ijnp.2015.073731

Investigations on structural, optical, morphological and electrical properties of nickel oxide nanoparticles

2015· article· en· W2282754025 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

VenueInternational Journal of Nanoparticles · 2015
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNon-blocking I/ONickel oxideMaterials scienceScanning electron microscopeNanoparticleTransmission electron microscopyAnalytical Chemistry (journal)Band gapDielectricOxideNanotechnologyChemistryOptoelectronicsMetallurgyComposite material

Abstract

fetched live from OpenAlex

Nickel oxide (NiO) nanoparticles have been prepared by chemical co-precipitation method. The synthesised nanoparticles were investigated by X-ray diffraction analysis (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-visible spectroscopy and dielectric studies. The formation of NiO nanoparticles was confirmed by X-ray diffraction (XRD). The morphology and size of the NiO nanoparticles were characterised using scanning and transmission electron microscopy (SEM and TEM). The optical properties were studied by the UV-visible absorption spectrum. The dielectric properties of NiO nanoparticles were studied in the frequency range of 50 Hz5 MHz at different temperatures. Further, electronic properties, such as valence electron plasma energy, average energy gap or Penn gap, Fermi energy and electronic polarisability of the NiO nanoparticles were calculated. The AC conductivity of the NiO nanoparticles increases with increase in temperature and frequency. The activation energy was calculated from AC conductivity studies.

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)0.001
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 score0.006
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.062
GPT teacher head0.286
Teacher spread0.224 · 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