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Record W1551009586 · doi:10.1115/1.1669414

Buoyancy Convection During the Growth of SixGe1−x by the Traveling Solvent Method (TSM)

2004· article· en· W1551009586 on OpenAlexafffundabout
M. Ziad Saghir, T. J. Makriyannis, D. Labrie

Bibliographic record

VenueJournal of Fluids Engineering · 2004
Typearticle
Languageen
FieldMaterials Science
TopicSolidification and crystal growth phenomena
Canadian institutionsDalhousie UniversityToronto Metropolitan University
FundersCanadian Space Agency
KeywordsBuoyancyConvectionMaterials scienceCrystal growthSolventSiliconMechanicsThermodynamicsCrystal (programming language)Heat transferNatural convectionChemistryPhysicsMetallurgy

Abstract

fetched live from OpenAlex

The traveling solvent method known as TSM is a process used to produce pure and homogeneous crystals structures. TSM has been tested on many alloys producing uniform and uncontaminated single crystals. In the present study the effect of buoyancy convection on the growth of the Si0.02Ge0.98 crystal grown by the traveling solvent method is investigated under different heating conditions. The full Navier-Stokes equations together with the energy and solutal equations are solved numerically using the finite element technique. The model takes into consideration the losses of heat by radiation and the use of the phase diagram to determine the silicon concentration at the growth interface. Results reveal a strong convection in the solvent, which in turn is detrimental to the growth uniformity in the crystal rod. Additional numerical results show that the convective heat transfer significantly influences the solute distribution in the liquid zone and affects the growth rate substantially. Qualitative comparison of the numerical results with the experiment conducted at Dalhousie University showed a good agreement for the silicon concentration at the growth interface.

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 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)0.001
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 score0.271
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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 teacher head, 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

Citations2
Published2004
Admission routes3
Has abstractyes

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