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Record W2332539260 · doi:10.1504/ijogct.2016.075850

Effect of initial coal particle size on coal liquefaction conversion

2016· article· en· W2332539260 on OpenAlexaffabout
Mehran Heydari, Moshfiqur Rahman, Rajender Gupta

Bibliographic record

VenueInternational Journal of Oil Gas and Coal Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLiquefactionAutoclaveParticle sizeTetralinCoalCoal liquefactionMaterials scienceParticle (ecology)Particle-size distributionWaste managementMineralogyChemistryChemical engineeringMetallurgyGeologyEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

In coal liquefaction process initial coal particle size can be considered as one of the important process parameters. In this work, particles of coal are prepared by pulverisation and separation into different particle size ranges below 45 to 1,000 µm. Since conventional batch autoclave is not suitable for short contact time experiments, as the time required for the autoclave to reach the reaction temperature can be substantial, the liquefaction runs were investigated with a rapid injection reactor designed specifically for investigating the effect of initial particle size on liquefaction conversion. A Canadian coal was examined in a tubular bomb reactor in presence of tetralin at 400°C for a short reaction time (5 min) with pressure of 6 MPa under nitrogen atmosphere. The results indicated that total conversion obtained during the liquefaction changed according to the different particle size, and optimum particle size (150-212 µm) was detected for the liquefaction condition. [Received: November 27, 2014; Accepted: August 22, 2015]

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 score0.209
Threshold uncertainty score0.253

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 head0.005
GPT teacher head0.249
Teacher spread0.244 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

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