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Record W1512215539

Nanoscale cF96 cubic versus icosahedral phase in devitrified Hf-based metallic glasses

2002· article· en· W1512215539 on OpenAlexvenueno aff
D. V. Louzguine, Min Seong Ko, Akihisa Inoue

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2002
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsnot available
Fundersnot available
KeywordsDevitrificationMaterials scienceIcosahedral symmetryAmorphous metalPhase (matter)CrystallographyAmorphous solidQuasicrystalDifferential scanning calorimetryCrystallizationMetallurgyChemical engineeringAlloyChemistryThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

The devitrification behaviour of the rapidly solidified quaternary hafnium-based alloys of Hf65NM17.5TM10Al7.5 composition (NM- noble metal, TM- 3d transition metal) was studied using differential scanning calorimetry. The purpose of the study was to evaluate the influence of composition on the devitrification products at the primary stage. The structure was analysed by using X-ray diffraction and transmission electron microscopy. The formation of the nanoparticles of the Hf-based quasicrystalline icosahedral or cubic cF96 Fd3−m Ti2Ni-type phase about 10 nm in size was observed at the primary devitrification stage in different metallic glasses with close compositions. The icosahedral phase consists of 137-atom Bergmann rhombic triacontahedra. The alloys in systems in which the stable Hf-based cF96 phase exists do not show the formation of the icosahedral phase from the amorphous matrix. The cF96 phase and the icosahedral phase formed by primary devitrification from the amorphous phase may inherit the local order of the icosahedral clusters in the amorphous matrix.

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)0.000
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.073
GPT teacher head0.286
Teacher spread0.214 · 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

Citations8
Published2002
Admission routes1
Has abstractyes

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