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Record W2053868336 · doi:10.1021/la9913046

Potential-Assisted Deposition of Alkanethiols on Au:  Controlled Preparation of Single- and Mixed-Component SAMs

2000· article· en· W2053868336 on OpenAlexaff
Fuyuan Ma, R. Bruce Lennox

Bibliographic record

VenueLangmuir · 2000
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsMcGill University
Fundersnot available
KeywordsMonolayerChemistryDeposition (geology)Self-assembled monolayerComponent (thermodynamics)AdsorptionChemical engineeringOpen-circuit voltageNanotechnologySolventOrganic chemistryMaterials scienceVoltage

Abstract

fetched live from OpenAlex

The commonly used method of preparing RS/Au self-assembled monolayers (SAMs) involves a passive incubation process in a nonabsorbing solvent. Preparation of mixed-component SAMs is particularly problematic under these conditions. The time course of the open circuit potential in the passive adsorption experiment suggests that control of the deposition potential could lead to a faster and ultimately more complete SAM formation process. This is shown to be the case, as both C 16 RS/Au SAMs and mixed C 16 /HOOCC 15 S/Au SAMs are shown to be readily prepared in approximately 15 min from 5 mM thiol solutions at potentials ranging from 200 to 600 mV (vs Ag/AgCl). The blocking properties of the resulting C 16 SAMs are excellent. This technique provides access to mixed-composition SAMs otherwise inaccessible using deposition under open circuit conditions.

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 score0.003

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 studies0.0000.000
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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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

Citations106
Published2000
Admission routes1
Has abstractyes

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