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Record W2162232379 · doi:10.1017/s0885715612000516

Miniaturization of mechanical milling for powder X-ray diffraction

2012· article· en· W2162232379 on OpenAlexafffund
Andrew J. Locock, David Chesterman, Diane Caird, M. John M. Duke

Bibliographic record

VenuePowder Diffraction · 2012
Typearticle
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsGrindingMaterials scienceTungsten carbideCorundumMetallurgyGrain size

Abstract

fetched live from OpenAlex

To enable mechanical milling of small (0.1–1.0 g) samples, a cylindrical grinding vessel machined from polypropylene and furnished with tungsten carbide rods has been designed and produced for use inside the conventional jar of a McCrone Micronizing Mill. The vessel is about one-seventh the volume of the conventional jar supplied by the manufacturer. The conditions of milling for both the conventional and the miniaturized-grinding assemblies were tested using quartz sand as a limiting case. The median grain sizes of the resultant powders were measured by an X-ray gravitational-sedimentation method, with contamination from the grinding media measured by Rietveld refinement and by instrumental neutron activation analysis. The use of tungsten carbide grinding elements permits rapid wet milling of a small sample to the same median grain size in about one-third of the time required by a regular sample ground in corundum. The relative contamination (by tungsten carbide on a weight basis) using the miniaturized-grinding assembly is about 6(1)% of the proportion of corundum contamination yielded by the conventional grinding assembly.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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

Citations23
Published2012
Admission routes2
Has abstractyes

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