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Record W2337732633 · doi:10.1039/9781849732017

Catalysis in the Refining of Fischer-Tropsch Syncrude

2010· book· en· W2337732633 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOxygenateFischer–Tropsch processRefining (metallurgy)CatalysisChemistryOrganic chemistrySelectivity

Abstract

fetched live from OpenAlex

Fischer-Tropsch Synthesis (FTS) has been used on a commercial scale for more than eighty years. It was initially developed for strategic reasons because it offered a source of transportation fuels that was independent from crude oil. Unlike crude, Fischer-Tropsch synthetic crude is rich in olefins and oxygenates, while being sulphur and nitrogen free. Consequently, the catalysis involved in refining it is significantly different and only a few catalysts have been developed for the purpose. Until now, an account of this topic has been missing from the literature, despite mounting interest in the technology. This is the first book to provide a review and analysis of the literature (journal and patent) on the catalysis needed to refine syncrude to transportation fuels. It specifically highlights the impact of oxygenates and how oxygenates affect selectivity and deactivation. This aspect is also related to the refining of biomass derived liquids. Topics covered include: dimerisation / oligomerisation, isomerisation / hydroisomerisation, catalytic cracking / hydrocracking and hydrogenation, catalytic reforming, aromatic alkylation, etherification, dehydration, and some oxygenate and wax specific conversions.

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.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.253
Threshold uncertainty score0.779

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 science0.0010.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.171
Teacher spread0.167 · 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

Quick stats

Citations132
Published2010
Admission routes1
Has abstractyes

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