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Record W1989781302 · doi:10.1063/1.3174929

Dynamics of chemically powered nanodimer motors subject to an external force

2009· article· en· W1989781302 on OpenAlexaff
Yu-Guo Tao, Raymond Kapral

Bibliographic record

VenueThe Journal of Chemical Physics · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDimerPropulsionMolecular dynamicsChemical reactionMolecular motorReactionMoleculeDynamics (music)Reaction coordinatePhysicsClassical mechanicsMechanicsChemical physicsMaterials scienceChemistryNanotechnologyComputational chemistryThermodynamicsQuantum mechanicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

The chemically powered self-propelled directed motions of nanodimer motors confined in a rectangular channel and subject to an applied external conservative force are investigated using hybrid molecular dynamics/multiparticle collision dynamics. The influence of factors, such as dimer sizes, chemical reaction type, and the nature of the interaction potentials between dimer monomers and solvent molecules, on the propulsion force and friction constant are examined. The stall force, for which the nanodimer has zero net velocity, and the thermodynamic efficiency of the motor are calculated. Both irreversible and reversible chemical reactions are considered. The simulation results are compared to theoretical predictions which are able to capture the major features of the self-propelled motion.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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 designTheoretical or conceptual
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

Citations37
Published2009
Admission routes1
Has abstractyes

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