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Record W4285492829 · doi:10.1002/cjce.24554

Adsorption‐hydration hybrid process for <scp>CO<sub>2</sub></scp> capture in a fixed bed of activated carbons

2022· article· en· W4285492829 on OpenAlexvenueno aff
Wen‐Xin Dai, Xi‐Yue Li, Dong‐Liang Zhong, Jin Yan, Kai Dong, Xiaoyan Deng

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsAdsorptionHydrateSaturation (graph theory)Activated carbonChemical engineeringClathrate hydrateChemistryMaterials scienceOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

Abstract This work reports an investigation of using a fixed bed of activated carbons (ACs) to capture CO2 at hydrate formation conditions. The experiments were conducted at 277.15 K and 3.5 MPa. The water saturation (WS) of the fixed bed of ACs varies from 0% to 100%. The results indicate that an adsorption‐hydration hybrid process occurred in the fixed bed of wet ACs while a single adsorption process occurred in the fixed bed of dry ACs. The adsorption‐hydration hybrid process performs better than the single adsorption process for CO2 capture. Gas consumption at 100% WS is 3.18 times greater than that obtained using dry ACs (single adsorption process). It is found that 40% WS is an optimal value, and the gas consumption obtained at this WS is larger than that obtained at 0%, 70%, and 100% WS. This gas consumption is also greater than that obtained using stirred reactors at the same temperature and pressure conditions, so the adsorption‐hydration hybrid process achieved in the fixed bed of wet ACs has a greater potential to capture CO2 in comparison with the single adsorption or hydrate formation 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 score0.002
Threshold uncertainty score0.005

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 head0.007
GPT teacher head0.189
Teacher spread0.182 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicCarbon Dioxide Capture TechnologiesFrench-language works237,207