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Record W2019459785 · doi:10.1196/annals.1292.014

TranSIESTA: A Spice for Molecular Electronics

2003· article· en· W2019459785 on OpenAlexfundno aff
Kurt Stokbro, Jeremy Taylor, Mads Brandbyge, Pablo Ordejón

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2003
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMolecular electronicsNanostructureElectrodeRing (chemistry)Molecular dynamicsMoleculeNanoscopic scaleSpiceDensity functional theoryElectrochemistryElectronicsConductanceScatteringAb initioMaterials scienceMolecular wireChemical physicsAb initio quantum chemistry methodsChemistryNanotechnologyComputational chemistryPhysicsElectronic engineeringCondensed matter physicsPhysical chemistryQuantum mechanics

Abstract

fetched live from OpenAlex

Our recently developed method, TranSIESTA, enables modelling of molecular electronic devices under operation conditions. The method is based on density functional theory, and calculates the self-consistent electronic structure of a nanostructure coupled to three-dimensional electrodes with different electrochemical potentials. It uses a full atomistic ab initio description of both the electrodes and the nanoscale device. The calculations reveal information about the scattering states, transmission coefficients, electron current, and non-equilibrium forces in the systems. In this paper we use the method to investigate the electrical properties of three ring phenyl-ethynylene oligomers (OPE). We present results for the electrical effect of side groups and molecular conformations of the molecules. The calculations indicate that molecular switching and negative differential conductance (NDC) are related to rotations of the middle phenyl ring.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.034
GPT teacher head0.282
Teacher spread0.249 · 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 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

Citations246
Published2003
Admission routes1
Has abstractyes

Explore more

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