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Record W2319312898 · doi:10.1515/1542-6580.2697

Effect of Operating Conditions for Higher Alcohols Synthesis from Synthesis Gas over Alkali-Modified Co-Rh-Mo Trimetallic Catalyst Supported on Multi-Walled Carbon Nanotubes

2011· article· en· W2319312898 on OpenAlexaff
Venkateswara Rao Surisetty, Janusz A. Koziński, Ajay K. Dalai

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2011
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsYork UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsSelectivityCatalysisSpace velocityMolar ratioEthanolAlkali metalCarbon nanotubeChemistryChemical engineeringMaterials scienceCarbon fibersInorganic chemistryNuclear chemistryNanotechnologyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The effects of operating conditions on the higher alcohols synthesis reaction from synthesis gas were studied in a single-pass tubular downflow fixed-bed reactor, using sulfided K-promoted trimetallic Co-Rh-Mo catalyst supported on multi-walled carbon nanotubes (MWCNTs). The p CO conversion increased monotonically with increasing reaction temperature (from 275 to 350°C) and pressure (from 800 to 1400 psi), while decreasing monotonically with increasing GHSV (from 2.4 to 4.2 m3 (STP)/(kg of cat./h)). To maximize the ethanol STY and selectivity, the optimum operating conditions were determined as 330°C, 1320 psi, and 3.8 m3 (STP)/kg of cat./h). Maximum ethanol STY and selectivity were obtained using gas with H2 to CO molar ratio around 1.25.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.288
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 source (direct Gemma or distilled Codex), 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

Citations2
Published2011
Admission routes1
Has abstractyes

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Same venueInternational Journal of Chemical Reactor EngineeringSame topicCatalysts for Methane ReformingFrench-language works237,207