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Record W7083163689 · doi:10.1093/ce/zkaf021

A review on coal pyrolysis and gasification: understanding the chemistries and influence of operating conditions

2025· article· en· W7083163689 on OpenAlexafffund

Bibliographic record

VenueClean Energy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsUniversity of Regina
FundersMitacsUniversity of Regina
KeywordsCoalPyrolysisCoal liquefactionSyngasCoal gasificationCarbochemistryCarbon fibersDestructive distillation

Abstract

fetched live from OpenAlex

Abstract Pyrolysis and gasification are two popular technologies that have been applied for coal utilization for centuries. In recent times, their applications for sustainable coal utilizations have attracted significant interest in hydrocarbon-based chemical synthesis, synthetic natural gas production, and carbon material synthesis. However, despite their long history in the coal industry, the underlying chemistries governing the pyrolysis and gasification processes are not well understood. This has contributed to why these technologies have yet to witness widespread commercialization in the coal industry. Therefore, the chemistries of coal pyrolysis and gasification were discussed in this review. It was found that the extent of primary pyrolysis reactions depends on hydrogen because hydrogen stabilizes the free radicals, and its absence slows down or stops the reactions. Operating conditions such as temperature and reactive atmospheres directly affect the pyrolytic reactions and the characteristics of the products, while pressure and particle size affect the mass transfer of volatile species and influence the extent of secondary pyrolysis reactions. In gasification, the composition of the syngas is principally determined by the water-gas-shift and methane-reforming reactions, while operating conditions such as temperature, catalysts, and choice of gasifying agents are used to control the characteristics of the syngas, dictated by the intended application.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.301
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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