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Аэродинамический высокопроизводительный распылитель жидких реагентов на основе сопла Лаваля

2020· article· ru· W3088977995 on OpenAlexaboutno aff
R Kleimanov, С. Е. Александров

Bibliographic record

VenueNanoindustry Russia · 2020
Typearticle
Languageru
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsReagentNozzleNebulizerVolumetric flow rateMaterials scienceCoaxialDesign for manufacturabilityAerodynamicsChemistryProcess engineeringMechanical engineeringEngineeringMechanicsAerospace engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Авторами статьи предлагается высокопроизводительное устройство для подачи жидкого реагента в установку для химического осаждения высокочистого кварца в пламени. Подача жидкого кремнийсодержащего реагента осуществляется путем преобразования его в аэрозоль при помощи аэродинамического распылителя с плоским соплом Лаваля с внутренним телом. Разработанная конструкция позволяет достичь больших расходов жидкого реагента путем изменения сечений сопла для регулировки скорости газа-распылителя. Предложенная конструкция отличается более высокой технологичностью и простотой изменения расхода реагента в широких пределах, в отличие от распространенных коаксиальных конструкций сопел. The authors propose a high-performance device for supplying a liquid reagent for the chemical vapor deposition of high-purity quartz. The liquid silicon-containing reagent is supplied by converting it into an aerosol using an aerodynamic nebulizer with a flat Laval nozzle incorporating an internal body. The developed design allows of achieving a high flow rate of the liquid reagent by changing the nozzle cross-sections so as to adjust the speed of the nebulizer gas. The proposed design features higher manufacturability and simple adjustment of the reagent flow rate over a wide range, as distinct from the common coaxial nozzle designs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.005

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 head0.019
GPT teacher head0.209
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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