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Record W7043493104

Theoretical study of nanoparticle formation in thermal plasma processing Nucleation, coagulation and aggregation

2008· dissertation· en· W7043493104 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge UdeS (Institutional Deposit of the University of Sherbrooke) · 2008
Typedissertation
Languageen
FieldEnvironmental Science
TopicCoagulation and Flocculation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThermophoresisNanoparticleParticle (ecology)Brownian motionNucleationFractalCoagulationCondensationPlasmaWork (physics)Evaporation
DOInot available

Abstract

fetched live from OpenAlex

This work presents a mathematical modeling study of the synthesis of nanoparticles in radio frequency (RF) inductively coupled plasma (ICP) reactors. The purpose is to further investigate the influence of process parameters on the final size and morphology of produced particles. The proposed model involves the calculation of flow and temperature fields of the plasma gas. Evaporation of raw particles is also accounted with the particle trajectory and temperature history calculated with a Lagrangian approach. The nanoparticle formation is considered by homogeneous nucleation and the growth is caused by condensation and Brownian coagulation. The growth of fractal aggregates is considered by introducing a power law exponent Df. Transport of nanoparticles occurs by convection, thermophoresis and Brownian diffusion. The method of moments is used to solve the particle dynamics equation. The model is validated using experimental results from plasma reactors at laboratory scale. The results are presented in the following manner. First, use is made of the computational fluid dynamics software (CFD), Fluent 6.1 with a commercial companion package specifically developped for aerosols named: Fine Particle Model (FPM). This package is used to study the relationship between the operating parameters effect and the properties of the end products at the laboratory scale. Secondly, a coupled hybrid model for the synthesis of spherical particles and fractal aggregates is developped in place of the FPM package. Results obtained from this model will allow to identify the importance of each parameter in defining the morphology of spherical primary particles and fractal aggregates of nanoparticles. The solution of the model was made using the geometries and operating conditions of existing reactors at the Centre de Recherche en Energie, Plasma et Electrochimie (CREPE) of the Université de Sherbrooke, for which experimental results were obtained experimentally. Additionally, this study demonstrates the importance of the flow and temperature fields on the growth of fractal particles; namely the aggregates.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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 designTheoretical or conceptual
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

Citations0
Published2008
Admission routes1
Has abstractyes

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