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Record W2887127434 · doi:10.1002/cjce.23329

Brown coal char CO<sub>2</sub>‐gasification kinetics with respect to the char structure part II: Kinetics and correlations

2018· article· en· W2887127434 on OpenAlexvenueno aff
Ziad Abosteif, Stefan Guhl, Bernd Meyer

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsCharCoalAdsorptionKineticsSpecific surface areaChemistryChemical engineeringVolume (thermodynamics)CombustionMaterials scienceThermodynamicsReaction rateChemical kineticsFluidized bedPhysical chemistryCatalysisOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Coal's physical structure is known to affect high‐temperature coal conversion processes such as gasification or combustion. This paper is Part II of the study of brown coal char structural changes during gasification. Firstly, German Lusatian brown coal was gasified in a laboratory‐scale fluidized bed reactor in CO 2 within a temperature range of 800–950 °C at atmospheric pressure. Then, physical structure properties were extensively evaluated by means of various techniques. Char specific surface area and its changes during gasification reaction were evaluated using N 2 and CO 2 physical adsorption techniques. Adsorption isotherms were also interpreted employing unconventional methods in order to obtain the specific surface areas of pores of different sizes. Gasification kinetics were evaluated employing three widely applied kinetic models: the random pore model (RPM), the volume reaction model (VM), and the shrinking core model (SCM). Finally, the instantaneous gasification reaction rate was correlated with the char structural properties at the corresponding conversion degrees. The closest linear correlation appeared between the gasification reaction rate and the specific surface area of mesopores (as determined by N 2 adsorption). Furthermore, correlations of the other structural properties with char conversion are provided. Observed structural changes were compared with the assumptions of the kinetic models.

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 score0.006
Threshold uncertainty score0.476

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 head0.007
GPT teacher head0.179
Teacher spread0.171 · 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
Published2018
Admission routes1
Has abstractyes

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