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Record W2175414367 · doi:10.1109/e3s.2015.7336809

Electromechanically actuating molecules

2015· article· en· W2175414367 on OpenAlexfundno aff
Wen Jie Ong, Ellen M. Sletten, Farnaz Niroui, Jeffrey H. Lang, Vladimir Bulović, Timothy M. Swager

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanotechnologyNanoscopic scaleMaterials scienceStictionQuantum tunnellingNanoelectromechanical systemsMolecular electronicsNanoelectronicsElectrodeLayer (electronics)Electrical conductorElectronicsOptoelectronicsMoleculeMicroelectromechanical systemsElectrical engineeringNanoparticleChemistryNanomedicine

Abstract

fetched live from OpenAlex

Controlled motion at the nanoscale is an emerging avenue for low powered electronics. The necessity for precision at the nanoscale makes organic chemistry an exciting addition to electronics, as organic synthesis is based upon the design and creation of nanoscale and sub-nanoscale structures. We have recently demonstrated the role of organic materials in the development of a nanoelectromechanical (NEM) switch that operates by electromechanical modulation of tunneling current through a switching gap defined by a few nanometer-thick organic molecular layer sandwiched between conductive contacts [1]. In this device, the molecular layer not only facilitates controlled formation of nanoscale switching gaps, but also avoids direct contact of the electrodes to minimize surface adhesion and provides force control at the nanoscale to prevent device failure due to stiction. Recent work has focused on the compression of the molecular layer by an applied electrostatic force between the two electrodes to reduce the tunneling gap. However, we envision next generation devices can contain advanced materials, which undergo electrochemically stimulated shape changes to modulate the tunneling distance and current. In order to achieve large current on-off ratios, the molecules must be capable of producing significant changes in dimension or shape upon electrical stimuli. Herein, we report a few examples of electromechanically actuating molecules.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.825
Threshold uncertainty score1.000

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)0.0010.000

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 head0.023
GPT teacher head0.259
Teacher spread0.237 · 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 teacher head, not a consensus.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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