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Record W3185957938 · doi:10.1002/cjce.24266

Experimental studies of catalyst deactivation due to carbon and sulphur during <scp>CO</scp> <sub>2</sub> reforming of <scp>CH</scp> <sub>4</sub> over Ni washcoated monolith in the presence of H <sub>2</sub> S

2021· article· en· W3185957938 on OpenAlexvenueno aff
Vivek Pawar, Prakash V. Ponugoti, Vinod M. Janardhanan, Srinivas Appari

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsnot available
Fundersnot available
KeywordsMonolithCordieriteCatalysisSulfurChemistryCarbon fibersDeposition (geology)BiogasFoulingCO poisoningChemical engineeringNuclear chemistryWaste managementMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract This study presents the CO 2 reforming of CH 4 over Ni coated monolith catalyst at 800°C and 101.325 kPa. The high CH 4 to CO 2 ratio employed in this study is similar to the CH 4 :CO 2 ratio of >1 found in biogas. Cordierite monolith samples (0.258 channels per m 2 ) washcoated with alumina are used for the experimental purpose. The study considers the combined deactivation effect due to sulphur poisoning and fouling due to carbon deposition. Four different cases with respect to the introduction and removal of H 2 S are considered. The rate of deactivation due to simultaneous carbon deposition and sulphur poisoning is much faster than the individual poisoning processes. The catalyst shows almost stable operation for 6 h without the presence of in the feed stream. From the conversion studies, it appears that the pre‐treatment of catalyst samples with H 2 S leads to negligible sulphur coverage. The sulphur poisoning effect is also found to be reversible.

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 score0.004

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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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Same venueThe Canadian Journal of Chemical EngineeringSame topicCatalysts for Methane ReformingFrench-language works237,207