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Atomic Partitioning of Ruthenium in Ni-Based Superalloys

2004· article· en· W2165630805 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials Characterization Techniques
Canadian institutionsUniversity of British Columbia
FundersDivision of Materials Sciences and EngineeringOak Ridge National LaboratoryUT-BattelleBattelleU.S. Department of Energy
KeywordsRutheniumSuperalloyMaterials scienceMetallurgyCatalysisMicrostructure

Abstract

fetched live from OpenAlex

The elemental partitioning characteristics of Ru additions within the microstructure of high refractory content Ni-base single crystal superalloys have been investigated using atom probe tomography (APT). Although detailed microanalysis revealed some dissolution of Ru within the ordered intermetallic precipitates, Ru was observed to preferentially partition to the disordered matrix. The partitioning characteristics of two nominally similar alloys with and without Ru were studied as part of this investigation. Analyses indicate that no significant changes in the partitioning characteristics of the constituent elements could be attributed to the presence of Ru for this particular set of alloys. The preferential site occupancy of Ru within the L1 2 lattice was also statistically quantified using ALCHEMI (atomic site location by channelling enhanced microanalysis). Interestingly, Ru exhibited a tendency to substitute for Al and occupy the corner sites in the structure.

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 score0.128
Threshold uncertainty score0.259

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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