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Record W2330429066 · doi:10.1002/cjce.22503

Performance of Cu/TiO<sub>2</sub>‐SiO<sub>2</sub> catalysts in hydrogenation of furfural to furfuryl alcohol

2016· article· en· W2330429066 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsnot available
FundersNortheast Petroleum UniversityNational Natural Science Foundation of China
KeywordsFurfuryl alcoholFurfuralCatalysisX-ray photoelectron spectroscopyMaterials scienceDispersityHydrothermal circulationChemical engineeringNuclear chemistryInorganic chemistryChemistryOrganic chemistryPolymer chemistry

Abstract

fetched live from OpenAlex

Abstract A series of Cu/TiO 2 ‐SiO 2 catalysts were prepared by a sol‐gel hydrothermal method and characterized by BET, SEM, TEM, XRD, XPS, and H 2 ‐TPR. The catalysts were used for selective hydrogenation of furfural to furfuryl alcohol. Results show that based on the Cu/SiO 2 catalyst, introducing a part of TiO 2 into the carrier while keeping very large specific surface area would promote the reduction of CuO, inhibit the growth of Cu crystal particles, and improve the dispersity of Cu particles in the catalyst. The electronegativity of Cu is enhanced in the double‐loaded Cu/TiO 2 ‐SiO 2 catalyst, compared with single‐loaded Cu/SiO 2 or Cu/TiO 2 catalysts. The Cu/TiO 2 ‐SiO 2 catalyst containing 0.40 g/g (40 wt%) TiO 2 in the carrier shows high furfural hydrogenation performance.

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.

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 score0.014
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.170
Teacher spread0.164 · 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