MétaCan
Menu
Back to cohort
Record W2093300832 · doi:10.1039/b004093m

Controlling organic reactions on silicon surfaces with a scanning tunneling microscope: Theoretical and experimental studies of resonance-mediated desorption

2000· article· en· W2093300832 on OpenAlexafffund
Saman Alavi, Roger Rousseau, Gregory P. Lopinski, Robert A. Wolkow, Q—Tamar Seideman

Bibliographic record

VenueFaraday Discussions · 2000
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsSteacie Institute for Molecular Sciences
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScanning tunneling microscopeDesorptionResonance (particle physics)SiliconQuantum tunnellingYield (engineering)Chemical physicsChemistryScanning tunneling spectroscopyMolecular physicsAtomic physicsMaterials scienceAnalytical Chemistry (journal)NanotechnologyPhysical chemistryOptoelectronicsAdsorptionOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

The dynamics of tip-induced, resonance-mediated bond-breaking in complex organic adsorbates is studied theoretically and experimentally. Desorption of benzene from a Si(100) surface is found to be efficient and sensitive to voltage, the measured yield rising from below 10(-10) to ca. 10(-6) per electron within a ca. 0.8 V range at low (< 100 pA) current. A theoretical model, based upon first principles electronic structure calculations and quantum mechanical wavepacket simulations, traces these observations to multi-mode dynamics triggered by a transition into a cationic resonance. The model is generalized to provide understanding of, and suggest a means of control over, the behaviour of different classes of organic adsorbates under tunneling current.

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 score0.002

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 studies0.0000.001
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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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

Citations40
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueFaraday DiscussionsSame topicMolecular Junctions and NanostructuresFrench-language works237,207