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Record W2544677206 · doi:10.1016/j.actamat.2016.10.031

Mixed mode growth of an ellipsoidal precipitate: Analytical solution for shape preserving growth in the quasi-stationary regime

2016· article· en· W2544677206 on OpenAlex
Daniel Larouche

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

VenueActa Materialia · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNucleationMaterials scienceConstant (computer programming)ThermodynamicsPrecipitationEllipsoidMatrix (chemical analysis)Binary numberGrowth ratePhysicsMathematicsGeometryComposite material

Abstract

fetched live from OpenAlex

The growth of an ellipsoidal precipitate has been analysed in the mixed-mode regime for a binary system. Under the assumption that the precipitate grows with constant eccentricities, an analytical solution was developed giving the time evolution of the size of the precipitate and the non-equilibrium concentration of the solute in the matrix. The mathematical analysis revealed that the evolution of the growth is characterized by a constant k called the interface migration coefficient. This coefficient was found to be equal to 12υc/ac, where ac is the critical size of nucleation and υc is the maximum growth velocity attainable with the applied driving force. This velocity, which was found to be proportional to the square root of the interface mobility, was assumed to be constant during the nucleation stage, making ac/υc to be the nucleation time. This finding suggests that there is a close link between the nucleation time and the mobility of the interface separating the nucleus from the 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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.041
GPT teacher head0.275
Teacher spread0.234 · 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