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Record W7055649512

Copper doped ceria catalyst prepared by reverse microemulsion method for thermocatalytic conversion of carbon dioxide via reverse water gas shift

2023· dissertation· en· W7055649512 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCatalysisMicroemulsionCarbon monoxideCopperNanoparticleWater-gas shift reactionX-ray photoelectron spectroscopyDesorption
DOInot available

Abstract

fetched live from OpenAlex

High surface area CeO2/Al2O3 nano-catalysts were synthesized via the reverse microemulsion method and evaluated for reverse water gas shift. The effect of the active phase dispersion on the CeO2 nanoparticle growth was investigated via X-ray diffraction and gas adsorption. The 47.9wt% CeO2/Al2O3 catalyst showed complete selectivity to CO generation while attaining nearly equilibrium values for CO2 conversion at 600 °C and 8,000 mL/(g h). As compared to bulk CeO2, nanoparticle growth in the CeO2/Al2O3 catalyst was hindered significantly, resulting in a relatively stable catalytic performance, similar to that of the bulk CeO2. Our findings reveal that the reverse microemulsion synthesized Al2O3 support significantly decreases CeO2 nanoparticle growth and agglomeration. This reduction in nanoparticle sintering contributes to the enhanced catalytic performance and stability, facilitating efficient CO2 reduction. \nCopper-doped ceria (CuCeO2) catalysts with 0-26.5 Cu/(Cu+Ce) at% were synthesized via the reverse microemulsion method. X-ray diffraction analysis of freshly synthesized and spent (post-reaction) catalysts showed no separate phase of copper or copper oxide, indicating that Cu was incorporated into the CeO2 lattice, replacing Ce. Temperature-programmed desorption experiments showed that the activation energy of CO2 desorption increased for higher Cu loadings, indicating stronger CO2 adsorption. This phenomenon was attributed to the enhanced formation of oxygen vacancies due to Cu doping. X-ray photoelectron spectroscopy further confirmed the enhanced generation of oxygen vacancies due to Cu incorporation. The catalytic performance showed that all catalysts were 100% selective to CO generation, with higher Cu loadings resulting in CO2 conversion close to equilibrium values. The activation energy of the reaction, determined through reaction tests, exhibited a linear relationship with the activation energy of CO2 desorption. The relationship between these two energy barriers is explored, providing valuable insights into the catalytic mechanisms for RWGS.

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 head0.211
Teacher spread0.203 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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