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Record W2072830554 · doi:10.1002/cvde.200706616

Multi‐scale Modeling and Constrained Sensitivity Analysis of Particulate CVD Systems

2007· article· en· W2072830554 on OpenAlexaff
C. M. White, G. Zeininger, Paul E. Ege, B. Erik Ydstie

Bibliographic record

VenueChemical Vapor Deposition · 2007
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsProcess Research Ortech (Canada)
Fundersnot available
KeywordsEconomies of agglomerationDiscretizationBreakageSensitivity (control systems)PopulationNucleationFluidized bedMechanicsExpression (computer science)Scale (ratio)Biological systemMathematicsMaterials scienceEnvironmental scienceStatistical physicsComputer sciencePhysicsEngineeringThermodynamicsMathematical analysisChemical engineering

Abstract

fetched live from OpenAlex

Abstract A finite‐dimensional, state‐space model of the discrete distribution function bypasses discretization of the continuous population balance, and facilitates simple modeling and fast numerical integration. An analytical expression describes the steady‐state, average particle diameter as a function of parameters such as nucleation, agglomeration, breakage, seed rate, and average seed particle diameter. The discrete population balance model is used to evaluate the analytical expression sensitivity to growth and decay phenomena such as nucleation, agglomeration, and breakage. The analytical expression is validated against data obtained from an industrial‐scale, fluidized bed, pilot reactor designed to produce solar‐grade silicon. The results indicate how the analytical expression describes a CVD‐type growth process, and also how the growth process may deviate due to the operating conditions.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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 designSimulation or modeling
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

Citations15
Published2007
Admission routes1
Has abstractyes

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