Bibliographic record
Abstract
The history of Thixomolding®, its technology and commercialization are reviewed along with recent evolution of new technology afforded by its metallurgical structure. Since Thixomolding was introduced in the early 1990’s, it has developed to more than 400 Thixomolding machines in the United States, Canada, Japan, China, Taiwan, Hong Kong, Malaysia, Korea, Germany, Belgium and France. Applications have been established in the electronics/communication, automobile, military, hand tool, medical and sporting goods markets. Thixomoldings principal advantages are in net-shaping, consolidation of parts, safety, environmental friendliness, mechanical properties and microstructure. The virtuous isotropic and fine-grained Thixomolded® microstructure has opened the door to derivative thermal mechanical processing for generating nanostructured Mg products of high strength/density along with improved ductility, fatigue strength, corrosion resistance and formability. This thermomechanical processing (TTMP) has been applied recently to the Thixomolded precursor to further refine the grain size and eutectic phases to nanometer sizes - providing yield strength above 300 MPa, fatigue strength of 150 MPa along with elongation of >10%. Alloys so processed include AZ50L, AZ60L, AM60, AZ61L, AZ70L-TH, AZ80, AZ91D, AXJ810-TH and Thixoblended® alloys of higher Zn content. Microstructure is related to processing and properties, as predestined by the Thixomolded microstructure. Fiber Metal Laminate composites based on this nanoMAG TTMP Mg product have demonstrated yield strength up to 900 MPa, with modulus of elasticity of 90 GPa.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".