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Theory and Technology of Semisolid Metal Molding

2008· article· en· W2048136617 on OpenAlexaff
Frank Czerwiński

Bibliographic record

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2008
Typearticle
Languageen
FieldEngineering
TopicInjection Molding Process and Properties
Canadian institutionsHusky Injection Molding Systems (Canada)
Fundersnot available
KeywordsMolding (decorative)ThixotropyMaterials scienceRaw materialExtrusionExtrusion mouldingSlurryMetal injection moldingMetallurgyLiquidusDie castingCastingComposite materialAlloySinteringChemistry

Abstract

fetched live from OpenAlex

Fundamentals of semisolid metal molding, including the particulate feedstock, methods of its generation and features that make it useful for processing, are outlined. Melting characteristics of the feedstock under sole influence of heat are considered, covering a wide range of microstructural and microchemical factors, believed to be of importance at high temperatures. The generation of the thixotropic slurry within the injection molding system and its solidification behaviour are accompanied by detailed features of the molded structures and their correlation with properties of net-shape components. In addition to conventional techniques the novel processing concepts including near-liquidus molding, semisolid extrusion molding as well as the alloy and composite generation in a semisolid state are described. An update on commercialization progress is completed by a characterization of the modern equipment used for process implementation with broad references to metal die casting and plastics injection molding.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.032
GPT teacher head0.267
Teacher spread0.235 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2008
Admission routes1
Has abstractyes

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Same venueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomenaSame topicInjection Molding Process and PropertiesFrench-language works237,207