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Record W1481736482 · doi:10.2172/899097

Compaction of Ceramic Microspheres, Spherical Molybdenum Powder and Other Materials to 3 GPa

2006· report· en· W1481736482 on OpenAlexaboutno aff
S R Carlson, B.P. Bonner, Frederick J. Ryerson, Michael Hart

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsnot available
FundersLawrence Livermore National LaboratoryU.S. Department of Energy
KeywordsMaterials scienceCompactionCeramicComposite materialPorosityGlass microsphereMolybdenumTitaniumSPHERESPowder metallurgyGranular materialSinteringMetallurgyMicrosphereChemical engineering

Abstract

fetched live from OpenAlex

Pressure-volume relationships were measured at room temperature for eight granular materials and one specimen of epoxy foam. The granular materials included hollow ceramic microspheres, spherical molybdenum powder, Ottawa sand, aluminum, copper, titanium and silicon carbide powders and glassy carbon spheres. Measurements were made to 0.9 GPa in a liquid medium press for all of the granular materials and to 3 GPa in a solid medium press for the ceramic microspheres and molybdenum powder. A single specimen of epoxy foam was compressed to 30 MPa in the liquid medium press. Bulk moduli were calculated as a function of pressure for the ceramic microspheres, the molybdenum powder and three other granular materials. The energy expended in compacting the granular materials was determined by numerically integrating pressure-volume curves. More energy was expended per unit volume in compacting the molybdenum powder to 1 GPa than for the other materials, but compaction of the ceramic microspheres required more energy per gram due to their very low initial density. The merge pressure, the pressure at which all porosity is removed, was estimated for each material by plotting porosity against pressure on a semi-log plot. The pressure-volume curves were then extrapolated to the predicted merge pressures and numerically integrated to estimate the energy required to reach full density for each material. The results suggest that the glassy carbon spheres and the ceramic microspheres would require more energy than the other materials to attain full density.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0190.000

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 head0.024
GPT teacher head0.293
Teacher spread0.269 · 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 teacher head, not a consensus.

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

Citations1
Published2006
Admission routes1
Has abstractyes

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