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Record W2057622281 · doi:10.1002/cjce.21771

An overview of conversion of residues from coal liquefaction processes

2013· article· en· W2057622281 on OpenAlexvenueno aff
Sameer Khare, Mark Dell’Amico

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCoal liquefactionAsphalteneLiquefactionCoalCarbochemistryChemistryWaste managementHeat of combustionResidue (chemistry)Chemical engineeringOrganic chemistryCombustionEngineering

Abstract

fetched live from OpenAlex

Abstract Direct coal liquefaction (DCL) is a process for converting coal to synthetic oils, which can be refined to make transportation fuels. Residue from this process contains inorganic material such as mineral matter originating from the coal and catalysts, and organic matter such as unconverted coal, heavy oils, pre‐asphaltenes and asphaltenes. The conversion of these DCL residues to lighter, high‐value products is an important step in helping to make this technology both commercially viable and environmentally acceptable. This paper provides an overview of the physico‐chemical characteristics and processing options available for coal liquefaction residues and compares and contrasts them to those of petroleum residues. Residue properties vary considerably, since they are highly dependent on feed coal, process configuration and operating conditions. Determination of composition and structural parameters of products derived from residue conversion can help determine their stability, coking and solvent hydrogen donating ability. Thermal conversion processes such as visbreaking and gasification offer the greatest promise for handling these heavy materials. The conversion chemistry, reactivity and kinetics of residue gasification are not well‐understood but are important in optimising hydrogen production for the process. The literature has been comprehensively reviewed to provide characteristics and properties of residues and their potential for conversion. In addition, the potential for producing high‐value carbon products from residues is briefly 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 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 score0.008
Threshold uncertainty score0.999

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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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

Citations38
Published2013
Admission routes1
Has abstractyes

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