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Record W2325776677 · doi:10.1021/nn400102m

Room Temperature Discrimination of Adsorbed Molecules and Attachment Sites on the Si(111)–7 × 7 Surface Using a qPlus Sensor

2013· article· en· W2325776677 on OpenAlexaff
Zsolt Majzik, Benedict Drevniok, Wojciech Kamiński, Martin Ondráček, A. B. McLean, Pavel Jelı́nek

Bibliographic record

VenueACS Nano · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsAdsorptionMaterials scienceMoleculeSurface (topology)Chemical physicsNanotechnologyCrystallographyChemistryPhysical chemistryGeometry

Abstract

fetched live from OpenAlex

In this paper, we show that simultaneous noncontact atomic force microscopy (nc-AFM) and scanning tunneling microscopy (STM) is a powerful tool for molecular discrimination on the Si(111)-7 × 7 surface, even at room temperature. Using density functional theory modeling, we justify this approach and show that the force response allows us to distinguish straightforwardly between molecular adsorbates and common defects, such as vacancies. Finally, we prove that STM/nc-AFM method is able to determine attachment sites of molecules deposited on semiconductor surface at room temperature.

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 score0.015
Threshold uncertainty score0.265

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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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