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Record W2121142228 · doi:10.1002/cjce.22370

Kinetics of reverse water‐gas shift reaction over Pt/Al<sub>2</sub>O<sub>3</sub> catalyst

2015· article· en· W2121142228 on OpenAlexvenueno aff
Suhas G. Jadhav, Prakash D. Vaidya, Bhalchandra M. Bhanage, Jyeshtharaj B. Joshi

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsnot available
FundersUniversity Grants Commission
KeywordsWater-gas shift reactionCatalysisMethanolSpace velocityChemistryRedoxChemical kineticsReaction rateCarbon dioxideKineticsWater gasSyngasChemical engineeringInorganic chemistrySelectivityOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The CAMERE (Carbon Dioxide Hydrogenation to Form Methanol via a Reverse Water‐Gas Shift Reaction) process for the transformation of CO2 into methanol comprises reverse water‐gas shift (RWGS) and methanol production. In this work, the reaction kinetics of RWGS was investigated using a commercial Pt/Al2O3 catalyst. Catalytic runs were accomplished in a fixed‐bed flow reactor at 0.1 MPa in the 573–873 K range. The space time was varied in the 0.03–0.25 g · h/L range. The prevalence of the chemical control regime was established. The influence of reaction variables on the catalyst performance was investigated, and it was found that the increase in pressure resulted in a growing CO2 conversion value. The reactor was operated under differential reaction conditions and the influence of the H2/CO2 ratio in the feed on reaction rates was studied. Finally, the reaction pathway was analyzed using the associative and redox reaction mechanisms, and the latter appeared dominant over Pt/Al2O3.

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 score0.002
Threshold uncertainty score0.003

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)0.0010.000

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 head0.011
GPT teacher head0.197
Teacher spread0.187 · 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

Citations25
Published2015
Admission routes1
Has abstractyes

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