MétaCan
Menu
Back to cohort
Record W2041750058 · doi:10.1002/cjce.20034

Direct oxidation of hydrogen sulphide to sulphur using impregnated activated carbon catalysts

2008· article· en· W2041750058 on OpenAlexaffvenue
Ajay K. Dalai, Michael T. Cundall, Mahuya De

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicIndustrial Gas Emission Control
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsActivated carbonCatalysisChemistrySulfurPotassium carbonateInorganic chemistryNuclear chemistryCarbon fibersMesoporous materialAmmonium iodideAdsorptionOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Abstract Low concentrations of H 2 S were directly oxidized to sulphur and small quantities of SO 2 , over seven different activated carbons with or without impregnation. The effectiveness of virgin activated carbon was tested at 175°C, 700 kPa, and O 2 /H 2 S ratio with 5% greater than stoichiometry. The conversion of H 2 S was 99.9 mol% with SO 2 production of 3–6%, for 360 min runtime for Fisher coconut shell activated carbon and 648 min for Envirotrol bituminous (EB) activated carbon. Then the activated carbons became deactivated due to deposition of sulphur on the surface. Under these conditions mesoporous activated carbons such as EB and Hydrodarco had the longest breakthrough time. The addition of 5.5 wt% ammonium iodide, potassium iodide and potassium carbonate individually to EB decreased the production of SO 2 while having minimal effect on the overall H 2 S conversion. The addition of 5.5 wt% NH 4 I decreased the average SO 2 production from 2.5% to 0.9%. The activation energy for the H 2 S oxidation on the 5.5 wt% NH 4 I on EB activated carbon was determined to be 40 kJ/mol.

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)0.0010.000
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 head0.016
GPT teacher head0.193
Teacher spread0.178 · 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

Citations10
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicIndustrial Gas Emission ControlFrench-language works237,207