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Record W2317294149 · doi:10.1021/jp211647e

Toward an Equation of State for Water inside Carbon Nanotubes

2012· article· en· W2317294149 on OpenAlexfundno aff
Mohsen Sadeghi, Gholamabbas Parsafar

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2012
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsnot available
FundersUniversity of British ColumbiaSharif University of Technology
KeywordsCarbon nanotubeState (computer science)Equation of stateMaterials scienceNanotechnologyEnvironmental scienceChemical engineeringChemical physicsThermodynamicsChemistryPhysicsMathematicsEngineering

Abstract

fetched live from OpenAlex

Water inside carbon nanotubes as an example of nanoconfined water has gained noticeable attention, in both theoretical and applied aspects. Molecular simulation has played a major role in the studies in this field. Yet, there is a need for systematic study of simulation results and compilation of scientifically reliable predictive relations. Here we present Monte Carlo simulations of water inside carbon nanotubes with different radii. An equation of state which was derived on the basis of the extended Lennard-Jones (12,6,3) as the effective pair potential is chosen for the system of water inside the carbon nanotubes. The equation of state is modified to take the effects of anisotropic pressure tensor into account. Using the simulation results, the applicability of this equation of state for water inside the carbon nanotubes is studied and the parameters of the equation of state for this system are obtained.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.235
Teacher spread0.209 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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