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Solidification of single droplets under combined cooling conditions

2016· article· en· W2316911351 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

VenueIOP Conference Series Materials Science and Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLiquidusMaterials scienceAlloyAluminiumMetallurgyDendrite (mathematics)Liquid nitrogenWater coolingComposite materialThermodynamicsChemistry

Abstract

fetched live from OpenAlex

In this study, a pneumatic high-temperature droplet generator was used to generate individual droplets (diameter range: 350 - 1200 μm) which were cooled under combined cooling conditions. The individual droplets were cooled in a nitrogen atmosphere after ejection and during subsequent free fall. After a defined falling distance, the particles were quenched in either oil or water to further increase their cooling rate. Two alloys in different temperature ranges were used to study the effect of different cooling conditions quantitatively by the analysis of different microstructural features. To show the working range of the droplet generator, a metallic glass FeCo35.1Nb7.7B4.3Si2.8 (liquidus: 1210 °C) was used as a high-temperature alloy, and its resulting amorphous fraction was quantified as an indicator for different cooling conditions. Furthermore, the aluminium alloy AlCu4.5 (liquidus: 650 °C) was solidified under different conditions and the subsequent secondary dendrite arm spacing (SDAS) measurements were analyzed.

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 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 score0.011
Threshold uncertainty score0.439

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)0.0000.000

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 head0.021
GPT teacher head0.215
Teacher spread0.194 · 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