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Record W2147048438 · doi:10.1073/pnas.1208699109

Conductivity of an atomically defined metallic interface

2012· article· en· W2147048438 on OpenAlexafffund
David J. Oliver, Jesse Maassen, Mehdi El Ouali, William Paul, Till Hagedorn, Yoichi Miyahara, Yue Qi, Hong Guo, Peter Grütter

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2012
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsNanoelectronicsMaterials scienceNanoindentationTungstenQuantum tunnellingThermal conductionSemiconductorScanning tunneling microscopeMolecular electronicsNanotechnologyGrapheneBallistic conductionOptoelectronicsCondensed matter physicsNanoscopic scaleElectronComposite materialChemistryPhysicsMetallurgy

Abstract

fetched live from OpenAlex

A mechanically formed electrical nanocontact between gold and tungsten is a prototypical junction between metals with dissimilar electronic structure. Through atomically characterized nanoindentation experiments and first-principles quantum transport calculations, we find that the ballistic conduction across this intermetallic interface is drastically reduced because of the fundamental mismatch between s wave-like modes of electron conduction in the gold and d wave-like modes in the tungsten. The mechanical formation of the junction introduces defects and disorder, which act as an additional source of conduction losses and increase junction resistance by up to an order of magnitude. These findings apply to nanoelectronics and semiconductor device design. The technique that we use is very broadly applicable to molecular electronics, nanoscale contact mechanics, and scanning tunneling microscopy.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.280
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

Citations27
Published2012
Admission routes2
Has abstractyes

Explore more

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