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Record W4394843523 · doi:10.1021/acs.langmuir.4c00315

Molecular Insights into the Dual Promotion–Inhibition Effects of NaCl at Various Concentrations on the CO<sub>2</sub> Hydrate Growth: A Molecular Simulation Study

2024· article· en· W4394843523 on OpenAlexaff
Han Jia, Fangning Fan, Qiuxia Wang, Zhihao Shen, Yuanbo Wang, Han Sun, Pingan Pei, Chuanqi Li, Kaihe Lv, Pan Huang

Bibliographic record

VenueLangmuir · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Alberta
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsDual (grammatical number)HydratePromotion (chess)ChemistryChemical engineeringFood scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Hydrate-based CO 2 storage in the ocean is considered a potential method for mitigating the greenhouse effect. Numerous studies demonstrated that NaCl exhibited the dual effects of promotion and inhibition in the nucleation and growth processes of CO 2 hydrate, whose mechanisms remain unclear. In this study, the effects of NaCl at various concentrations on the CO 2 hydrate growth and crystal are investigated. The independent gradient model based on Hirshfeld partition, electrostatic potential, and binding energy is conducted to study the interaction between ions and water molecules. The motion trajectories of ions are observed at the molecular level to reflect the impact of ion motion on hydrate growth. The results show that the influence of NaCl on hydrate growth depends on a delicate balance of dual promotion–inhibition effects. NaCl can combine more water molecules and provide a transport channel of CO 2 to promote hydrate growth at low concentrations. Meanwhile, the promoting effects shift toward inhibition with increasing NaCl concentrations. In a word, this paper proposes a novel mechanism for the dual promotion–inhibition effects of NaCl on hydrate growth, which is significant for further research on hydrate-based CO 2 storage in the ocean.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.222
Teacher spread0.216 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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