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Record W2164342252 · doi:10.1186/1556-276x-6-185

AFM-assisted fabrication of thiol SAM pattern with alternating quantified surface potential

2011· article· en· W2164342252 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

VenueNanoscale Research Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKelvin probe force microscopeMonolayerNanotechnologyAtomic force microscopySubstrate (aquarium)NanochemistryThiolSelf-assembled monolayerBiomoleculeMaterials scienceBiosensorFabricationScanning probe microscopyChemical physicsChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Thiol self-assembled monolayers (SAMs) are widely used in many nano- and bio-technology applications. We report a new approach to create and characterize a thiol SAMs micropattern with alternating charges on a flat gold-coated substrate using atomic force microscopy (AFM) and Kelvin probe force microscopy (KPFM). We produced SAMs-patterns made of alternating positively charged, negatively charged, and hydrophobic-terminated thiols by an automated AFM-assisted manipulation, or nanografting. We show that these thiol patterns possess only small topographical differences as revealed by AFM, and distinguished differences in surface potential (20-50 mV), revealed by KPFM. The pattern can be helpful in the development of biosensor technologies, specifically for selective binding of biomolecules based on charge and hydrophobicity, and serve as a model for creating surfaces with quantified alternating surface potential distribution.

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 score0.152
Threshold uncertainty score0.477

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 head0.042
GPT teacher head0.268
Teacher spread0.227 · 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