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Numerical simulation of a continuous sonoreactor for cotton cellulose residues recovery

2025· article· en· W4411040252 on OpenAlexafffund
Pierre Dal, Julie Kring, Dalma Schieppati, Daria C. Boffito

Bibliographic record

VenueUltrasonics Sonochemistry · 2025
Typearticle
Languageen
FieldMaterials Science
TopicUltrasound and Cavitation Phenomena
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCelluloseChemistryChemical engineeringOrganic chemistryMaterials sciencePolymer sciencePolymer chemistryPulp and paper industryEngineering

Abstract

fetched live from OpenAlex

Numerical simulations are a tool for sonoreactors design and reaction parameters choice. We modeled a two parts sonoreactor with six lateral flat transducers along the walls and a concentric high intensity focused ultrasound (HIFU) transducer at the bottom. We examined the effects of the gap between the reflector and transducers ( h ), cone radii in the lower part and ultrasound frequency ( f ) on the cavitation activity of cellulose esters solutions. Then, we investigated the effects of the properties of cellulose solutions on the cavitation activity The simulation accounts for the attenuation due to the cavitation bubbles and considers the propagation of sound waves from the HIFU as linear. We measured the speed of sound in the cellulose esters solutions and included it in our simulations: 1545 m s −1 for 6.25 g L -1 . h , f , the density ( ρ ) and the viscosity ( μ ) of the cellulose solutions have the most significant effects − accounting for 34 % to 61 % of the variance − on the total acoustic pressure ( p T ) and active cavitation surface area ( V ). p T and V increase as f and ρ increase, and as h and μ decrease. At 78 kHz and h = 0.075 m, with μ = 5.3 × 10 -3 Pa.s and ρ = 941.8 kg m −3 , the simulation resulted in the highest p T and largest V : 1.96 × 10 6 Pa and 3.99 × 10 −2 m 2 . These data provide a basis to optimize sonoreactor design and operating conditions for enhanced cavitation performance in cellulose processing.

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)0.001
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 score0.033
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.009
GPT teacher head0.263
Teacher spread0.254 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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