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Record W4377143153 · doi:10.1016/j.fuel.2023.128715

Characterization of soot emissions formed in a compression ignition engine cofired by ammonia and diesel

2023· article· en· W4377143153 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFuel · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsNational Research Council CanadaUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Research Council
KeywordsSootDiesel fuelDiesel exhaustMaterials scienceDiesel engineGreenhouse gasCarbon fibersChemical engineeringCombustionChemistryOrganic chemistryComposite materialAutomotive engineeringComposite number

Abstract

fetched live from OpenAlex

The impact of ammonia (NH 3 ) co-firing with diesel on the greenhouse gases (GHG) and soot emissions of compression ignition (CI) engines is a current concern in large-scale agriculture, marine transportation and shipping applications for which NH 3 is proposed as a near-term decarbonization solution. In this study, the effect of NH 3 port injection on the GHG emissions and the characteristics of the soot formed in a NH 3 -diesel dual fuel CI engine is investigated. Soot is sampled from the engine exhaust operating in dual-fuel mode at 20% and 40% NH 3 energy fraction and in diesel-only mode at a fixed engine speed, load, and diesel injection strategy. Detailed analysis of soot is done to investigate: the exhaust soot yield using gravimetric analysis, soot growth and inception through the average primary particles size and number concentration using analysis of Transmission Electron Microscopy (TEM) imaging, the soot nanostructure using Raman spectroscopy, and the chemical composition using X-ray Photoelectron Spectroscopy (XPS). The engine GHG emissions measurements shows that carbon dioxide (CO 2 ) is reduced while N 2 O emissions increases with NH 3 addition. The engine soot emissions yield is significantly reduced with the average primary particles size and number concentration decreasing as the NH 3 energy fraction increases. The soot nanostructure is impacted by NH 3 addition as it becomes more graphitic with high ratio of sp2 to sp3 carbon bonding. The XPS chemical composition analysis also shows an increase in the nitrogen bonding with carbon in the aromatic rings on the particles surface. The results suggest that the chemical interaction of NH 3 with diesel results in soot with more graphitic nanostructure as nitrogen reaction with carbon at active defect sites leads to an increase in the nitrogen content on the soot surface with NH 3 addition. This indicates an increased potential of NH 3 co-firing with diesel to form nitrogenated PAHs (N-PAH) on the soot surface which would require further studies to identify the risks posed on the environment and human health.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.363

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 head0.013
GPT teacher head0.241
Teacher spread0.227 · 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