MétaCan
Menu
Back to cohort
Record W3004124477 · doi:10.1002/cjce.23716

Chemical‐looping gasification of coal with CuFe<sub>2</sub>O<sub>4</sub> oxygen carriers: The reaction characteristics and structural evolution

2020· article· en· W3004124477 on OpenAlexvenueno aff
Mei An, Qingjie Guo, Jingjing Ma, Xiude Hu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsnot available
Fundersnot available
KeywordsChemical looping combustionSyngasInertAdsorptionCoalDesorptionChemical engineeringOxygenChemical reactionHematiteCarbon fibersCoal gasificationChemistryScanning electron microscopeMaterials scienceInert gasMineralogyCatalysisComposite materialPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract In this study, coal gasification to produce synthesis gas by chemical looping was investigated with CuFe2O4 oxygen carriers (OCs), including the reaction characteristics and structural evolution process. It was found that the presence of a CuFe2O4 OC increases the gasification reaction rate of coal in comparison to the use of inert bed material (silica sand). The CuFe2O4 OC enhanced the performance of hematite and improved the ability to produce syngas of CuO OCs. During the chemical looping process, CuFe2O4 was reduced to Fe3O4 and Cu. Furthermore, N2 adsorption/desorption and scanning electron microscopy images verified that the released O2 and the generated CO2 by the CuFe2O4 OCs improved the carbon conversion and facilitated the pore opening and expansion shown by the increase in specific surface area. This can be used as a theoretical reference that can be used to gain a better understanding of the microscopic mechanism for how CuFe2O4 OCs can accelerate the chemical looping gasification of coal.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.166
Teacher spread0.159 · 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

Citations24
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicChemical Looping and Thermochemical ProcessesFrench-language works237,207