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Formation and Decomposition Kinetics of CO <sub>2</sub> Hydrates under Static and Stirred Conditions

2025· article· en· W4415980227 on OpenAlexaff
Ting Huang, Bo Yang, Qiang Fu, Shi Chen, Qingshuang Zhang, Xiaobin Li, Bohui Shi, Shangfei Song, Rui Qin, Haiyuan Yao

Bibliographic record

VenueEnergy & Fuels · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsPetro-Canada
FundersScience Foundation of China University of Petroleum, BeijingNational Natural Science Foundation of China
KeywordsDissociation (chemistry)HydrateDecompositionStatic mixerContinuous stirred-tank reactorKineticsKinetic energyClathrate hydrate

Abstract

fetched live from OpenAlex

In the context of global climate change and energy transition strategies, the CO 2 hydrate technology has emerged as a promising solution in carbon sequestration and energy storage. This study systematically examines the formation and dissociation kinetics of CO 2 hydrates in pure water systems using a high-pressure reactor under both static and stirred conditions. Key experimental observations reveal distinct phase behavior: under static conditions, a continuous CO 2 hydrate membrane with no obvious macroscopic pores is formed, with no visible bubble penetration or membrane surface damage observed, creating significant mass transfer barriers, while the introduction of a gas–liquid phase connecting tube promotes both membrane thickening and bulk hydrate formation. In contrast, stirred systems generate dispersed hydrate particles that exhibit either slurry-type or crystalline morphology. Kinetic analysis shows that, under identical conditions, the hydrate formation conversion rate of stirred systems is twice that of static systems, significantly improving the formation efficiency, and finally, its formation amount is nearly twice that of static systems. For dissociation kinetics, the decomposition rate of stirred systems is twice that of static systems under the same decomposition temperature. At the same decomposition pressure, the decomposition rate of the stirred system is 5 times that of the static system. Dissociation characteristics differ markedly between systems. Static conditions produce membrane sedimentation, while stirred systems show bubble-induced optical clearing. The driving force of static system shows the characteristics of “first rising and then stabilizing at a high level”, while the driving force of the stirred system shows the dynamic characteristics of “sudden rise and decay to stability” and finally achieves system balance. These findings offer valuable insights for advancing CO 2 -hydrate-based technologies in energy and environmental applications.

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 head0.006
GPT teacher head0.234
Teacher spread0.228 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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