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Record W3003683904 · doi:10.1002/aic.16936

Highly selective absorption separation of H<sub>2</sub>S and CO<sub>2</sub> from CH<sub>4</sub> by novel azole‐based protic ionic liquids

2020· article· en· W3003683904 on OpenAlexaff
Xiaomin Zhang, Wenjie Xiong, Lingling Peng, Youting Wu, Xingbang Hu

Bibliographic record

VenueAIChE Journal · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsMinistry of Education and Child Care
FundersFundamental Research Funds for the Central UniversitiesNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsIonic liquidSolubilityChemistrySelectivityAzoleBar (unit)Absorption (acoustics)Ionic bondingReaction mechanismPhysical chemistryOrganic chemistryCatalysisMaterials scienceIon

Abstract

fetched live from OpenAlex

Abstract Recently, the selective removal of H2S and CO2 has been highly desired in natural gas sweetening. Herein, four novel azole‐based protic ionic liquids (PILs) were designed and prepared through one‐step neutralization reaction. The solubility of H2S (0–1.0 bar), CO2 (0–1.0 bar), and CH4 (0–5.0 bar) was systematically measured at temperatures from 298.2 to 333.2 K. NMR and theoretical calculation were used to investigate the reaction mechanism between these PILs and H2S. Reaction equilibrium thermodynamic model (RETM) was screened to correlate the H2S solubility. Impressively, 1,5‐diazabicyclo[4,3,0] non‐5‐ene 1,2,4‐1H‐imidazolide ([DBNH][1,2,4‐triaz]) shows the highest H2S solubility (1.4 mol/mol or 7.3 mol/kg at 298.2 K and 1.0 bar) and superior H2S/CH4 (831) and CO2/CH4 (199) selectivities compared with literature results. Considering the excellent absorption capacity of H2S, high H2S/CH4, and CO2/CH4 selectivity, acceptable reversibility, as well as facile preparation process, it is believed that azole‐based PILs provide an attractive alternative in natural gas upgrading process.

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)0.0010.000

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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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

Citations162
Published2020
Admission routes1
Has abstractyes

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