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Record W2021496454 · doi:10.1021/ie0507124

The Hydration Behavior of Partially Sulfated Fluidized Bed Combustor Sorbent

2005· article· en· W2021496454 on OpenAlexaff
Jinsheng Wang, Yinghai Wu, Edward J. Anthony

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSorbentChemical engineeringChemistrySulfationFluidized bed combustionWork (physics)Particle (ecology)Fluidized bedMass transferCombustorThermodynamicsChromatographyCombustionAdsorptionOrganic chemistryGeology

Abstract

fetched live from OpenAlex

The efficiency of limestone sorbent utilization in fluidized bed combustors (FBCs) is low, because of incomplete sulfation of CaO. Hydration of the FBC ash can reactivate the partially sulfated sorbent, and the hydrated ash can be reinjected into the combustors as the SO 2 sorbent. In this work, the rate of hydration, which is of primary importance in the reactivation process, is studied for FBC ash. The effects of major rate factors, temperature and particle size, are analyzed. At ambient temperature, the degree of hydration is well below 100% after 4 h of testing, suggesting the existence of a barrier to the complete conversion of CaO. The particle size effect on hydration rate appears to be complex, but can be interpreted in terms of the effects of heat and mass transfer. A model is proposed that gives a consistent description of the hydration behavior, and methods for enhancing the hydration are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.070
GPT teacher head0.313
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2005
Admission routes1
Has abstractyes

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