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Record W2086603159 · doi:10.1021/jp071290+

Monolayer-Directed Electrodeposition of Oxide Thin Films:  Surface Morphology versus Chemical Modification

2007· article· en· W2086603159 on OpenAlexafffund
Dinah M. Soolaman, Hua‐Zhong Yu

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2007
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMonolayerMorphology (biology)OxideSurface modificationMaterials scienceChemical engineeringThin filmNanotechnologyChemistryMetallurgy

Abstract

fetched live from OpenAlex

In this paper we describe the general role that surface morphology and chemical nature play in guiding the cathodic deposition of oxide thin films onto electrode surfaces. By use of a “featureless” stamp for microcontact printing (μCP), the pregrooved microfeatures (“mountains” and “valleys” representing the track trails) of recordable compact disc (CD-R) gold substrates can be selectively modified with OH- or CH 3 -terminated self-assembled monolayers (SAMs). For comparison, “flat” gold substrates were patterned with the above SAMs in parallel “microstrips” that are analogous to the CD-R substrate (but no height differences). Electrochemical deposition of zirconia thin films showed that, on the CD-R substrates, surface morphology (height difference) dominates over the blocking effects of the SAMs; that is, deposition occurred primarily on the mountains despite these sites being modified with organic monolayers. For flat gold substrates it was found that n -alkanethiolate SAMs block deposition in modified areas while directing the deposition to regions of the bare surface. When flat gold substrates were modified with CH 3 - and OH-terminated SAMs in alternating microstrips, deposition was confined to “narrower” regions that are different from the periodicity on the stamp. The type of microstructures and feature sizes of the zirconia thin film were dependent on scan rate, number of cycles, and terminal groups of the SAM to a lesser extent.

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 score0.012
Threshold uncertainty score0.293

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 head0.226
Teacher spread0.219 · 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

Citations17
Published2007
Admission routes2
Has abstractyes

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