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Record W2314529093 · doi:10.1021/ef5014192

Behavior of Sulfur during the Pyrolysis of Tires

2015· article· en· W2314529093 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

VenueEnergy & Fuels · 2015
Typearticle
Languageen
FieldEngineering
TopicIndustrial Gas Emission Control
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSulfidationSulfurSelectivityPyrolysisChemistryFlue-gas desulfurizationCharIsothermal processPhase (matter)Inorganic chemistryChemical engineeringOrganic chemistryThermodynamicsCatalysis

Abstract

fetched live from OpenAlex

The mechanisms of transfer of sulfur to the volatile phase and char phase during the pyrolysis of tires have been investigated by complementing the available literature data with TGA experiments. For isothermal experiments, the global selectivity expression could be simplified into an intrinsic form of sulfur loss selectivity, which is solely a function of temperature. Two other phenomena have been found to influence the intrinsic sulfur loss selectivity: solid matrix desulfurization and metals sulfidation. In the case where tires would contain no metals and pyrolysis was performed at a temperature of 400°C or higher, decomposition kinetics is limiting and the intrinsic sulfur loss selectivity would converge to the value of 1. Below 350 °C, mass transfer limitation will promote solid matrix desulfurization, producing sulfur loss selectivity greater than 1. Over 350 °C, if zinc and/or steel are present in tires, sulfidation will cluster sulfur in the solid phase and sulfur loss selectivity will become lower than 1. A developed form of sulfur loss selectivity could be obtained to account for these phenomena.

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 score0.011
Threshold uncertainty score0.270

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 head0.018
GPT teacher head0.219
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