MétaCan
Menu
Back to cohort
Record W2914776718 · doi:10.1149/ma2018-02/9/532

Charge Transport and Practical Applications of All-Carbon Molecular Electronic Devices

2018· article· en· W2914776718 on OpenAlexaff
Mustafa Supur, Amin Morteza Najarian, Adam Johan Bergren, Richard L. McCreery

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGrapheneCarbon fibersMolecular electronicsMaterials scienceGraphene nanoribbonsRaman spectroscopyNanotechnologyMolecular orbitalMolecular wireMoleculeChemical physicsChemistryOrganic chemistryPhysicsOpticsComposite material

Abstract

fetched live from OpenAlex

Molecular electronic junctions can be made by covalently bonding aromatic molecules and graphene ribbons to a flat, sp2 hybridized carbon electrode followed by a “top contact” of electron-beam deposited carbon. The entire active region of the structure consists of carbon and hydrogen, and electronic properties range from insulators to efficient conductors, with excellent lifetime and tolerance to temperature excursions. 1-3 Of particular interest is a carbon/graphene/carbon device containing 5-carbon wide graphene ribbons, which avoids torsional disorder common to aromatic molecular components (shown schematically below, left). The graphene devices have the highest molecular conductance reported to date for large-area molecular junctions, and is stable for at least five million current/voltage cycles to ±4 A/cm2. 4 An application of all-carbon molecular tunnel junctions in electronic music will be described, which resulted in the first known commercial product involving molecular electronics (below, right). 5 (1) Morteza Najarian, A.; Bayat, A.; McCreery, R. L.; Orbital Control of Photocurrents in Large Area All-Carbon Molecular Junctions; Journal of the American Chemical Society 2018, 140, 1900. (2) Supur, M.; Smith, S. R.; McCreery, R. L.; Characterization of Growth Patterns of Nanoscale Organic Films on Carbon Electrodes by Surface Enhanced Raman Spectroscopy; Analytical Chemistry 2017, 89, 6463. (3) Morteza Najarian, A.; McCreery, R. L.; Structure Controlled Long-Range Sequential Tunneling in Carbon-Based Molecular Junctions; ACS Nano 2017, 11, 3542. (4) Supur, M.; Van Dyck, C.; Bergren, A. J.; McCreery, R. L.; Bottom-up, Robust Graphene Ribbon Electronics in All-Carbon Molecular Junctions; ACS Applied Materials & Interfaces 2018, 10, 6090. (5) Bergren, A. J.; Zeer-Wanklyn, L.; Semple, M.; Pekas, N.; Szeto, B.; McCreery, R. L.; Musical molecules: the molecular junction as an active component in audio distortion circuits; Journal of Physics: Condensed Matter 2016, 28, 094011. Figure 1

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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.234
Teacher spread0.227 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicMolecular Junctions and NanostructuresFrench-language works237,207