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Record W2095309001 · doi:10.1039/c4nr06180b

On the mechanical and electronic properties of thiolated gold nanocrystals

2014· article· en· W2095309001 on OpenAlexaff
Kacem Smaali, Simon Desbief, Giuseppe Foti, Thomas Frederiksen, Daniel Sánchez‐Portal, A. Arnau, J. P. Nys, Philippe Leclère, D. Vuillaume, Nicolas Clément

Bibliographic record

VenueNanoscale · 2014
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsNovelis (Canada)
FundersAgence Nationale de la Recherche
KeywordsMaterials scienceMonolayerQuantum tunnellingNanocrystalDipoleFinite element methodCoupling (piping)ModulusMolecular dynamicsNanotechnologyCoatingNanoparticleChemical physicsOptoelectronicsComposite materialComputational chemistryChemistryStructural engineering

Abstract

fetched live from OpenAlex

We present a quantitative exploration, combining experiment and simulation, of the mechanical and electronic properties, as well as the modifications induced by an alkylthiolated coating, at the single nanoparticle (NP) level. We determined the response of the NPs to external pressure in a controlled manner using an atomic force microscope tip. We found a strong reduction in their Young's modulus, as compared to bulk gold, and a significant influence of strain on the electronic properties of the alkylthiolated NPs. Electron transport measurements of tiny molecular junctions (NP/alkylthiol/CAFM tip) show that the effective tunnelling barrier through the adsorbed monolayer strongly decreases by increasing the applied load, which translates in a remarkable and unprecedented increase in the tunnel current. These observations are successfully explained using simulations based on the finite element analysis (FEA) and first-principles calculations that permit one to consider the coupling between the mechanical response of the system and the electric dipole variations at the interface.

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 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 score0.019
Threshold uncertainty score0.192

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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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.

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

Citations29
Published2014
Admission routes1
Has abstractyes

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