MétaCan
Menu
Back to cohort
Record W2015286625 · doi:10.1063/1.2908078

Design of chemically propelled nanodimer motors

2008· article· en· W2015286625 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Chemical Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDimerMesoscopic physicsSPHERESNon-equilibrium thermodynamicsChemical physicsHard spheresMoleculeMolecular dynamicsClassical mechanicsMotion (physics)ChemistryMolecular motorMolecular physicsPhysicsAtomic physicsComputational chemistryMaterials scienceNanotechnologyThermodynamicsQuantum mechanicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

The self-propelled motion of nanodimers fueled by a chemical reaction taking place under nonequilibrium steady state conditions is investigated. The nanodimer consists of a pair of catalytic and chemically inactive spheres, in general with different sizes, with a fixed internuclear separation. The solvent in which the dimer moves is treated at a particle-based mesoscopic level using multiparticle collision dynamics. The directed motion of the dimer can be controlled by adjusting the interaction potentials between the solvent molecules and the dimer spheres, the internuclear separation, and sphere sizes. Dimers can be designed so that the directed motion along the internuclear axis occurs in either direction and is much larger than the thermal velocity fluctuations, a condition needed for such nanodimers to perform tasks involving targeted dynamics.

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.

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 score0.061
Threshold uncertainty score0.318

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 head0.022
GPT teacher head0.219
Teacher spread0.198 · 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