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SCANNING TUNNELING MICROSCOPY MANIPULATION OF COMPLEX ORGANIC MOLECULES ON SOLID SURFACES

2006· article· en· W2124952870 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.

Bibliographic record

VenueAnnual Review of Physical Chemistry · 2006
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsScanning tunneling microscopeMoleculeChemical physicsNanotechnologyAdsorptionRectificationScanning probe microscopyQuantum tunnellingMaterials scienceChemistryPhysicsOrganic chemistryOptoelectronics

Abstract

fetched live from OpenAlex

Organic molecules adsorbed on solid surfaces display a fascinating variety of new physical and chemical phenomena ranging from self-assembly and molecular recognition to nonlinear optical properties and current rectification. Both the fundamental interest in these systems and the promise of technological applications have motivated a strong research effort in understanding and controlling these properties. Scanning tunneling microscopy (STM) and, in particular, its ability to manipulate individual adsorbed molecules, has become a powerful tool for studying the adsorption geometry and the conformation and dynamics of single molecules and molecular aggregates. Here we review selected case studies demonstrating the enormous capabilities of STM manipulations to explore basic physiochemical properties of adsorbed molecules. In particular, we emphasize the role of STM manipulations in studying the coupling between the multiple degrees of freedom of adsorbed molecules, the phenomenon of molecular molding, and the possibility of creating and breaking individual chemical bonds in a controlled manner, i.e., the concept of single-molecule chemistry.

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 score0.011
Threshold uncertainty score0.501

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 head0.255
Teacher spread0.248 · 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