MétaCan
Menu
Back to cohort

Fischer–Tropsch Process

2013· other· en· W2101442387 on OpenAlexaff
Arno de Klerk

Bibliographic record

VenueKirk-Othmer Encyclopedia of Chemical Technology · 2013
Typeother
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFischer–Tropsch processSyngasGas to liquidsSyngas to gasoline plusOxygenateRefining (metallurgy)LiquefactionCatalysisCoal liquefactionChemistryChemical engineeringProcess engineeringWaste managementOrganic chemistrySteam reformingEngineeringHydrogen productionSelectivity

Abstract

fetched live from OpenAlex

Abstract A Fischer–Tropsch process always forms part of a larger indirect liquefaction facility, which consists of three processing steps. The first step is to convert a carbon source, such as coal, natural gas, biomass, or organic waste, into synthesis gas (syngas). Syngas is a mixture of hydrogen and carbon monoxide, and it is the feed material for a Fischer–Tropsch process, which is the second step in the indirect liquefaction process. Fischer–Tropsch synthesis is the catalytic polymerization and hydrogenation of CO, which produces a synthetic crude oil (syncrude). The syncrude is a multiphase mixture of hydrocarbons, oxygenates, and water. The third step is the refining of the syncrude to products that are traditionally produced from conventional crude oil, such as transportation fuels and petrochemicals. The current contribution deals only with the Fischer–Tropsch process; the generation of syngas and the refining of Fischer–Tropsch syncrude are not discussed in any detail. A Fischer–Tropsch process has three main elements: catalyst, reactor, and gas loop. Fischer–Tropsch catalysis is described to explain the relationship among the different catalyst types, operating conditions, and products. A description of the main syncrude types and their compositions is also provided. Fischer–Tropsch technologies are discussed, with an explanation of the relationship between catalyst and reactor, the tradeoffs involved in different catalyst–reactor combinations, as well as guidelines for technology selection. The role of the Fischer–Tropsch gas loop is outlined, with a discussion of the key elements of the gas loop and how they affect the overall performance of a Fischer–Tropsch process.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0340.017

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 head0.236
Teacher spread0.231 · 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
GenreOther

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

Citations50
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueKirk-Othmer Encyclopedia of Chemical TechnologySame topicCatalysts for Methane ReformingFrench-language works237,207