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Record W2035315493 · doi:10.1021/nn1001694

Water Transport with a Carbon Nanotube Pump

2010· article· en· W2035315493 on OpenAlexaff
Wenhui Duan, Quan Wang

Bibliographic record

VenueACS Nano · 2010
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCarbon nanotubeNanotubeMoleculeChemical physicsMolecular dynamicsMaterials scienceWater transportNanotechnologyMomentum (technical analysis)ChemistryEnvironmental scienceWater flowComputational chemistryEnvironmental engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Transportation of water molecules in a carbon nanotube based on an energy pump concept is investigated by molecular dynamics simulations. A small portion of the initially twisted wall of a carbon nanotube is employed to function as an energy pump for possible smooth transportation of water molecules. The momentum and resultant force on a water molecule and the corresponding displacement and velocity of the molecule are particularly studied to disclose the transportation process. The efficiency of the transportation is found to be dependent on the size of the energy pump. Once the process for the transportation of one molecule is elucidated, transportations of 20 water molecules are simulated to investigate the effect of the environmental temperature and fluctuations in the nanotube channel on the transportation. It is revealed that the accelerated period of multiple water molecules is longer than that in the transportation of a single water molecule. In addition, the fluctuations in the nanotube wall due to the buckling propagation and a higher environmental temperature will all lead to obvious decreases in the water velocity and hence retard the transportation process.

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 score0.033
Threshold uncertainty score0.607

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 head0.005
GPT teacher head0.173
Teacher spread0.168 · 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

Citations88
Published2010
Admission routes1
Has abstractyes

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