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Record W2329252947 · doi:10.1021/ef101154d

Red Mud as a Catalyst for the Upgrading of Hemp-Seed Pyrolysis Bio-oil

2010· article· en· W2329252947 on OpenAlexaff
Elham Karimi, Cédric Briens, Franco Berruti, Sina Moloodi, Tommy Tzanetakis, Murray J. Thomson, Marcel Schlaf

Bibliographic record

VenueEnergy & Fuels · 2010
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsUniversity of TorontoWestern UniversityUniversity of Guelph
Fundersnot available
KeywordsDeoxygenationPyrolysisCatalysisChemistryRed mudOrganic chemistryAqueous solutionChemical engineeringNuclear chemistry

Abstract

fetched live from OpenAlex

Hemp-seed pyrolysis bio-oil was upgraded in a batch laboratory-scale pressure reactor under 800 psi (cold) hydrogen gas at 350−365 °C using a non-alkaline, nontoxic Fe x O y /SiO 2 /TiO 2 catalyst [reduced red mud (RRM)] obtained by the reduction of red mud with HOAc/HCCOH. The upgraded liquid obtained was separated into stable organic and aqueous phases. Comparative analyses between the crude oil and the organic and aqueous phases of upgraded products showed that the RRM-upgraded bio-oil is composed of fewer carbonyl-containing and polar oxygenated compounds but more saturated hydrocarbons. The upgraded oil phases are less viscous than the native oil and stable against resin formation for at least 60 days. The catalytic activity of RRM is related to its ability to catalyze both deoxygenation and cracking reactions that convert reactive components (aldehydes, ketones, and carboxylic acids), which make the oil unstable over time, into less reactive deoxygenated products.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 science0.0000.000
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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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

Citations71
Published2010
Admission routes1
Has abstractyes

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