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Study on the Volatiles and Kinetic of in-Situ Catalytic Pyrolysis of Swelling Low-Rank Coal

2017· article· en· W2773837917 on OpenAlexaff
Chao He, Xiaojian Min, Huaan Zheng, Yingjie Fan, Qiuxiang Yao, Dan Zhang, Xing Tang, Chong Wan, Ming Sun, Xiaoxun Ma, Charles Q. Jia

Bibliographic record

VenueEnergy & Fuels · 2017
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of Toronto
FundersNorthwest UniversityNational Natural Science Foundation of China
KeywordsSwellingChemistryCoalPyrolysistar (computing)Fourier transform infrared spectroscopyMetal ions in aqueous solutionMethanolCatalysisYield (engineering)Chemical engineeringSolventCoal tarThermogravimetric analysisNuclear chemistryChromatographyOrganic chemistryMaterials scienceIonComposite material

Abstract

fetched live from OpenAlex

A new method combined solvent swelling with an in-situ catalytic effect of metal ions was developed and introduced in coal pyrolysis to increase the coal conversion and the tar yield as well as to improve the quality of the tar products. Low-rank coal of Shendong coal from China was used to investigate the effect of demineralization, swelling, and in-situ catalysis on pyrolysis reactivity and kinetic characteristics, yield distribution of products, and the tar composition. The experiments were performed using a thermogravimetric analyzer/Fourier transform infrared spectrometer (TG-FTIR), pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), and a fixed-bed reactor to examine the pyrolysis behavior of raw coal, demineralized coal, methanol swelling demineralized coal, and methanol swelling with metal ions (Ca 2+, Cu 2+, and Co 2+ ) in-situ-impregnated coal, respectively. The results showed that coal conversion could be promoted by pretreatment of solvent swelling and in-situ-impregnated Cu 2+ and Co 2+ ions, respectively. The gas evolution results of FTIR indicated that the in-situ loading of Cu 2+ and Co 2+ ions had a catalytic effect on the evolution of CO 2, CH 4, and aromatics of the swollen coal. The tar yield of demineralized coal was improved by the methanol-swelling pretreatment. With the in-situ loading of Cu 2+ and Co 2+ ions, the tar yield of swelling coal further increased by 16.80% and 28.75%. The composition of tar analyzed by Py-GC/MS indicated that methanol swelling increased the relative content of the acidic compounds and also had a positive effect on the yields of PCX (phenol, cresol, xylenol). The in-situ loading of metal ions increased the relative content of the aromatic compounds but had a different effect on the formation of BTXN (benzene, toluene, xylene, and naphthalene). The Cu 2+ and Co 2+ ions had a catalytic effect on phenols decomposition during coal pyrolysis, resulting in a decrease of the relative content of the acidic compounds dramatically. The kinetic results showed that the in-situ impregnation of Ca 2+, Cu 2+, and Co 2+ ions into the swollen coal could result in a decrease of the activation energy and pre-exponential factor at the corresponding temperature range of the first and the second prolysis stage. In addition, a possible mechanism on in-situ catalytic pyrolysis of swelling coal was discussed and proposed based on the evolution and composition of the evolved species investigated during pyrolysis. The impregnation of the metal ions may catalyze the primary reactions and secondary reactions during coal pyrolysis.

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)0.0000.000

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 head0.012
GPT teacher head0.216
Teacher spread0.203 · 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".

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Citations44
Published2017
Admission routes1
Has abstractyes

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