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The effect of sodium chloride on the charge state of soot particles in a laminar diffusion flame

2024· article· en· W4402030119 on OpenAlexafffund
Olanrewaju W. Bello, Mohsen Kazemimanesh, Larry W. Kostiuk, Jason S. Olfert

Bibliographic record

VenueCombustion and Flame · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSootLaminar flowDiffusion flameDiffusionSodiumChemistryCombustionAnalytical Chemistry (journal)ThermodynamicsEnvironmental chemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

• The study focuses on soot particle charge state and how soot evolves in flames. • The impact of NaCl on methane flame was investigated. • A well-studied Santoro burner was utilized to produce a stable laminar diffusion flame. • A charging model was employed to estimate the impact of NaCl on ion concentrations. • Soot particle size and formation differ between methane and methane-NaCl flames. This study investigates the effect of sodium chloride on the charge state of soot nanoparticles formed in a laminar diffusion flame by measuring the soot particle size distribution, average charge per particle, and charge fraction at various heights within the flame. The well-studied Santoro burner with methane as the fuel (at 0.35 L/min) and co-flow air (at 70 L/min) was used, which produced a stable laminar diffusion flame with flame height of 61 mm. Samples of soot nanoparticles were extracted via a 0.3 mm orifice in a 3-mm stainless steel tubular probe at various heights above the burner and were immediately diluted by a factor of a few thousand for aerosol measurement. The effect of sodium chloride on a methane flame was investigated by comparing the experimentally measured data for methane-only and methane-NaCl flames. The addition of NaCl particles to the laminar diffusion flame did not have a significant effect on the particles in the nucleation region of the flame. The majority of the incipient soot particles in both flames are uncharged, and their sizes are nearly the same, with diameters of approximately 5 nm or less. However, the size of soot particles differs by approximately 10 % to 25 % between methane-only and methane-NaCl flames in the coagulation-dominated region of the flame. The net charge on soot particles within the coagulation region of the methane-only flames is negative, while it is positive with NaCl addition. The fraction of charged particles and ion concentration decreases with NaCl addition within the coagulation region. The study indicates that the smaller particle size observed in methane-NaCl flames may be attributed to reduced coagulation via altered particle charge states. These factors could be the major contributor to the variations in soot formation between methane-only and methane-NaCl flames. This research addresses a notable knowledge gap concerning the influence of NaCl, a prevalent component of hydraulic fracturing fluids, on soot particle behaviour in flames. By explaining the impact of NaCl on soot formation and charge states, the findings contribute to a deeper understanding of combustion processes in environments influenced by hydraulic fracturing operations, thereby informing strategies for reducing emissions and improving environmental sustainability in energy production. Overall, this article represents a significant advancement in the field of combustion science, with implications for environmental stewardship in energy production. This study provides valuable insights into how the introduction of NaCl alters the electrostatic properties of soot particles. This investigation expands upon existing knowledge by shedding light on the intricate mechanisms underlying soot formation and evolution in the presence of NaCl, elucidating its potential implications for combustion processes involving fossil fuels and industrial flaring.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.147

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.204
Teacher spread0.197 · 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
Published2024
Admission routes2
Has abstractyes

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