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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

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 score0.071
Threshold uncertainty score0.418

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 head0.007
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