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Record W2591425530 · doi:10.3390/catal7020069

Effect of CO Concentration on the α-Value of Plasma-Synthesized Co/C Catalyst in Fischer-Tropsch Synthesis

2017· article· en· W2591425530 on OpenAlexaff
James Aluha, Yongfeng Hu, Nicolas Abatzoglou

Bibliographic record

VenueCatalysts · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsCanadian Light Source (Canada)Université de Sherbrooke
Fundersnot available
KeywordsFischer–Tropsch processSyngasCatalysisSpace velocityHydrocarbonChemistryIsothermal processSelectivityWaxDiesel fuelMolar ratioCobaltNuclear chemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

A plasma-synthesized cobalt catalyst supported on carbon (Co/C) was tested for Fischer-Tropsch synthesis (FTS) in a 3-phase continuously-stirred tank slurry reactor (3-φ-CSTSR) operated isothermally at 220 °C (493 K), and 2 MPa pressure. Initial syngas feed stream of H2:CO ratio = 2 with molar composition of 0.6 L/L (60 vol %) H2 and 0.3 L/L (30 vol %) CO, balanced in 0.1 L/L (10 vol %) Ar was used, flowing at hourly space velocity (GHSV) of 3600 cm3·h−1·g−1 of catalyst. Similarly, other syngas feed compositions of H2:CO ratio = 1.5 and 1.0 were used. Results showed ~40% CO conversion with early catalyst selectivity inclined towards formation of gasoline (C4–C12) and diesel (C13–C20) fractions. With prolonged time-on-stream (TOS), catalyst selectivity escalated towards the heavier molecular-weight fractions such as waxes (C21+). The catalyst’s α-value, which signifies the probability of the hydrocarbon chain growth was empirically determined to be in the range of 0.85–0.87 (at H2:CO ratio = 2), demonstrating prevalence of the hydrocarbon-chain propagation, with particular predisposition for wax production. The inhibiting CO effect towards FTS was noted at molar H2:CO ratio of 1.0 and 1.5, giving only ~10% and ~20% CO conversion respectively, although with a high α-value of 0.93 in both cases, which showed predominant production of the heavier molecular weight fractions.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.277
Teacher spread0.263 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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