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Record W2324971754 · doi:10.1017/s0885715613001188

Crystalline domain size and faulting in the new NIST SRM 1979 zinc oxide

2013· article· en· W2324971754 on OpenAlexaff
James P. Cline, Matteo Leoni, David R. Black, Albert Henins, John E. Bonevich, Pamela S. Whitfield, Paolo Scardi

Bibliographic record

VenuePowder Diffraction · 2013
Typearticle
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsDiffractometerMaterials scienceCrystalliteNISTTransmission electron microscopyScintillatorStackingOpticsAnalytical Chemistry (journal)MineralogyNanotechnologyScanning electron microscopeDetectorMetallurgyComposite materialChemistryPhysicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

A NIST SRM certified to address the issue of crystallite size measurement through a line profile analysis has been under development for several years. In order to prepare the feedstock for the SRM, nano-crystalline zinc oxide was produced from thermal decomposition of zinc oxalate. The thermal processing parameters were chosen to yield particles in two size ranges, one with a distribution centered at approximately 15 nm and another centered at 60 nm. Certification data were collected on a NIST-built diffractometer equipped with a Johansson incident beam monochromator and scintillation detector. Data were analyzed using whole powder pattern modeling to determine microstructural data. The analysis shows domains to be in the form of discs of a fairly small aspect ratio. While both materials exhibit the effects of stacking faults through broadening of specific hkl reflections, their presence in the 60 nm is more difficult to discern. Images of the crystallites obtained with transmission electron microscopy are consistent with the results from the X-ray diffraction analyses.

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)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.245
Teacher spread0.234 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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