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Record W2973115838 · doi:10.1021/acs.cgd.9b00870

Diversity in Crystal Growth Dynamics and Crystal Morphology of Structure-H Hydrate

2019· article· en· W2973115838 on OpenAlexaff
Riku Matsuura, Shunsuke Horii, Saman Alavi, Ryo Ohmura

Bibliographic record

VenueCrystal Growth & Design · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Ottawa
FundersJapan Society for the Promotion of ScienceJKA Foundation
KeywordsHydrateMethylcyclohexaneCrystal (programming language)Crystal growthPhase (matter)CrystallographyClathrate hydrateChemistryMethaneCrystal structureMorphology (biology)Chemical physicsMaterials scienceChemical engineeringGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

This paper demonstrates the diversity in crystal growth dynamics and crystal morphology of structure-H hydrate formed with methane and methylcyclohexane (MCH) correlated to the driving force. ΔTsub, which is the difference between the experimental temperature of the crystal growth and the phase equilibrium temperature, was used as an index of the driving force. At ΔTsub = 1.6 and 3.2 K, hydrate crystals were initially formed at the water/MCH interface and grew into the hydrate film covering the interface. After the entire interface was covered by the hydrate film, the hydrate growth stopped. The shape of individual hydrate crystals was polygonal. The size of hydrate crystals was smaller with increasing ΔTsub. At ΔTsub = 5.3 K, the first hydrate crystals were observed at the water/MCH interface and crystals grew not only along the interface but also toward the interior of MCH phase, even after the water/MCH interface was completely covered by the hydrate film. The dendritic hydrate crystals were observed at the interface at ΔTsub = 5.3 K. The implications of these observations on crystal morphology on determining the conditions for methane capture for the purpose of storage and transportation are discussed.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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.

Study designObservational
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

Citations14
Published2019
Admission routes1
Has abstractyes

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