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Record W2155028878 · doi:10.1073/pnas.2430913100

Thermodynamic stability of hydrogen clathrates

2003· article· en· W2155028878 on OpenAlexaff
Serguei Patchkovskii, John S. Tse

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsClathrate hydrateHydrogenBar (unit)MoleculeChemistrySofteningHydrogen bondHydrogen storageChemical stabilityThermodynamicsComputational chemistryChemical physicsPhysical chemistryCrystallographyMaterials sciencePhysicsHydrateOrganic chemistry

Abstract

fetched live from OpenAlex

The stability of the recently characterized type II hydrogen clathrate [Mao, W. L., Mao, H.-K., Goncharov, A. F., Struzhkin, V. V., Guo, Q., et al. (2002) Science 297, 2247-2249] with respect to hydrogen occupancy is examined with a statistical mechanical model in conjunction with first-principles quantum chemistry calculations. It is found that the stability of the clathrate is mainly caused by dispersive interactions between H2 molecules and the water forming the cage walls. Theoretical analysis shows that both individual hydrogen molecules and nH2 guest clusters undergo essentially free rotations inside the clathrate cages. Calculations at the experimental conditions--2,000 bar (1 bar = 100 kPa) and 250 K confirm multiple occupancy of the clathrate cages with average occupations of 2.00 and 3.96 H2 molecules per D-5(12) (small) and H-5(12)6(4) (large) cage, respectively. The H2-H2O interactions also are responsible for the experimentally observed softening of the H[bond]H stretching modes. The clathrate is found to be thermodynamically stable at 25 bar and 150 K.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.027
GPT teacher head0.262
Teacher spread0.234 · 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 designSimulation or modeling
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

Citations200
Published2003
Admission routes1
Has abstractyes

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