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Record W3132035177 · doi:10.1002/cjce.24083

Sewage sludge ashes as a primary catalyst for the abatement of tar in biomass gasification: Bubbling versus spouted‐fluidized bed configuration

2021· article· en· W3132035177 on OpenAlexvenueno aff
Giovanna Ruoppolo, Francesco Miccio, Michele Miccio, Paola Brachi, Riccardo Chirone

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsFluidized bedtar (computing)SyngasElutriationWaste managementNozzleFluidizationSewage sludgeCharVolumetric flow rateMaterials scienceChemistryEnvironmental engineeringEnvironmental scienceCatalysisSewage treatmentCoalMechanicsThermodynamicsEngineering

Abstract

fetched live from OpenAlex

Abstract Sewage sludge (SS) ashes, rich in iron and calcium, have been tested as a primary catalyst during air gasification of commercial wood pellets in a pre‐pilot scale fluidized bed (FB) reactor. The shifting from a conventional fluidized bed to a spouted‐fluidized bed configuration has been assessed on the catalyst performance. Specifically, at constant total air inlet flow rate, two different values of the air flow rate in a central spouting nozzle have been adopted, which correspond to 20% and 37.5% of the total inlet gas flow rate. Under the conventional fluidized bed configuration (i.e., bubbling regime), SS ashes exhibit good performance in term of tar reduction (about 20% decrease compared to a bed of inert silica sand), without significantly affecting the syngas composition. Concerning the transition to the spouted‐fluid bed configuration, the gas‐solid contact efficiency is enhanced at lower air flow rates through the central nozzle, with respect to the FB regime, leading to better gasification performance in terms of tar reduction (around 40% less) and syngas quality. A slightly worse gasification performance is obtained at high values of air flow rate in the central nozzle, due to a progressive increase of gas bed bypassing. Furthermore, moving from the conventional FB configuration to the spouted‐fluid bed one dramatically boosts the elutriation rate of carbon fines as well as the attrition of catalyst particles.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.457

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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicThermochemical Biomass Conversion ProcessesFrench-language works237,207