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Record W4229081365 · doi:10.1021/acsami.2c01959

Reverse Microemulsion-Synthesized High-Surface-Area Cu/γ-Al<sub>2</sub>O<sub>3</sub> Catalyst for CO<sub>2</sub> Conversion via Reverse Water Gas Shift

2022· article· en· W4229081365 on OpenAlex
Anastasiia Zakharova, Muhammad Waqas Iqbal, Edris Madadian, David S. A. Simakov

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.

Bibliographic record

VenueACS Applied Materials & Interfaces · 2022
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCatalysisMicroemulsionCalcinationMaterials scienceSelectivityWater-gas shift reactionSpace velocityChemical engineeringAnalytical Chemistry (journal)ChemistryChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Reverse microemulsion method was implemented to synthesize a CuO/γ-Al2O3 catalyst (18 wt % Cu) with a specific surface area (SSA) of 328 m2/g (after calcination at 400 °C). Catalytic performance was evaluated in the range of temperatures and space velocities (300–600 °C and 10,000–200,000 mL/(g h)). The catalyst was 100% selective to CO generation while attaining a nearly equilibrium CO2 conversion at 500 °C (ca. 50% at 10,000 mL/(g h) and H2/CO2 = 4). Despite the initial reduction of surface area under the reaction conditions, the reduced Cu/γ-Al2O3 catalyst demonstrated a stable performance for 80 h on stream, attaining a nearly equilibrium CO2 conversion at 600 °C (ca. 60% at 60,000 mL/(g h) and H2/CO2 = 4). The selectivity to CO generation remained complete during the stability test, and no significant carbon deposition was detected.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.214
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