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Record W2130806399 · doi:10.1139/cjc-2014-0537

Methane hydrate formation in a test sediment of sand and clay at various levels of water saturation

2015· article· en· W2130806399 on OpenAlexvenueno aff
Asheesh Kumar, Tushar Sakpal, Sudip Roy, Rajnish Kumar

Bibliographic record

VenueCanadian Journal of Chemistry · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersCouncil of Scientific and Industrial Research, India
KeywordsHydrateBentoniteClathrate hydrateMethaneSaturation (graph theory)ChemistryChemical engineeringClay mineralsPore water pressureMineralogyGeologyGeotechnical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Kinetics of methane hydrate formation with different ratios of silica sand and clay and different water saturations were studied. At suitable temperature and methane gas pressure, water in the void spaces of silica sand packing and intercalated area of clay were converted into hydrate. It was observed that the rate of hydrate formation increases with higher void space in the packing, and addition of clay in test sediment decreases water to hydrate conversion as well as rate of hydrate formation. Maximum water to hydrate conversion of 60.0% was achieved in pure silica sand bed at 75% water saturation. Presence of fine clay particles is expected to reduce the void spaces and thus may hinder effective mass transfer of hydrate forming gases in the bed. However, it is also possible that the bentonite clay used in this work may actually inhibit hydrate growth. Additional experiments in stirred tank reactor were carried out to understand the inhibiting effect of bentonite clay for hydrate formation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.200
Teacher spread0.187 · 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 teacher head, 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

Citations130
Published2015
Admission routes1
Has abstractyes

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