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Record W1994747781 · doi:10.1155/2015/750689

Synthesis of CuNi/C and CuNi/<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mo>γ</mml:mo></mml:mrow></mml:math>-Al<sub>2</sub>O<sub>3</sub>Catalysts for the Reverse Water Gas Shift Reaction

2015· article· en· W1994747781 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsX-ray photoelectron spectroscopyCatalysisAlloyPolyolMaterials scienceYield (engineering)MetalNuclear chemistryAnalytical Chemistry (journal)Chemical engineeringMetallurgyChemistryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

A new polyol synthesis method is described in which CuNi nanoparticles of different Cu/Ni atomic ratios were supported on both carbon and gamma-alumina and compared with Pt catalysts using the reverse water gas shift, RWGS, reaction. All catalysts were highly selective for CO formation. The concentration of CH 4 was less than the detection limit. Cu was the most abundant metal on the CuNi alloy surfaces, as determined by X-ray photoelectron spectroscopy, XPS, measurements. Only one CuNi alloy catalyst, Cu 50 Ni 50 /C, appeared to be as thermally stable as the Pt/C catalysts. After three temperature cycles, from 400 to 700°C, the CO yield at 700°C obtained using the Cu 50 Ni 50 /C catalyst was comparable to that obtained using a Pt/C catalyst.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.125
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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