MétaCan
Menu
Back to cohort
Record W2316790607 · doi:10.1515/ijcre-2012-0033

Reforming of Glycerol into Bio-Crude: A Parametric Study

2013· article· en· W2316790607 on OpenAlexaff
Matthew Tymchyshyn, Zhongshun Yuan, Chunbao Xu

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsWestern University
Fundersnot available
KeywordsGlycerolChemistryRaw materialYield (engineering)CharCatalysisDilutionExtraction (chemistry)HydrogenChemical engineeringChromatographyOrganic chemistryNuclear chemistryMaterials sciencePyrolysis

Abstract

fetched live from OpenAlex

Abstract The reforming of glycerol was investigated using a micro-reactor in the presence of MoCoP/zeolite catalyst. The parameters which were investigated include initial hydrogen pressure, reaction temperature, residence time, and feedstock concentration. The liquid products were separated into water-soluble components and bio-oil by liquid-liquid extraction with water and ethyl acetate. The bio-oil, gaseous products, char, and unreacted glycerol were quantified relative to the initial mass of glycerol feed. The composition of the bio-oil was determined by GC/MS. The optimum conditions for the reforming of glycerol into bio-crude in the presence of MoCoP/zeolite catalyst were found to be: 300°C reaction temperature, 5 MPa initial hydrogen pressure, 60 min reaction time, and 100% glycerol feed. While dilution of the glycerol feedstock with water had a negative effect on bio-oil yield, reforming of pure glycerol produced the highest bio-oil yield (40 wt.% at 300°C, 1 h, and 5 MPa H 2 ). The amount of char deposited on the catalyst decreased with extended reaction time, increased reaction temperature, and elevated initial hydrogen pressure.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.212
Teacher spread0.207 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Chemical Reactor EngineeringSame topicCatalysis for Biomass ConversionFrench-language works237,207