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Record W2765253026 · doi:10.1002/admt.201700159

An Application of Diazonium‐Induced Anchoring Process in the Fabrication of Micro‐Electromechanical Systems

2017· article· en· W2765253026 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

VenueAdvanced Materials Technologies · 2017
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsMiQro Innovation Collaborative CentreMcGill University
Fundersnot available
KeywordsSilanizationMaterials scienceSubstrate (aquarium)FabricationLayer (electronics)NanotechnologyGraftingChemical engineeringComposite materialPolymer

Abstract

fetched live from OpenAlex

Abstract In situ generation of diazonium cations and their subsequent reduction and grafting is a versatile technique to modify a variety of substrates. In the absence of a conducting substrate, the grafting of aminophenylene layer can be achieved with assistance of a reducing agent (diazonium‐induced anchoring process—DIAP). Here, a systematic investigation of the possible effect of the type substrate on the thickness of aminophenyl layer is carried out using Fe powder reducing agent. The study is carried out on three different substrates: p‐doped Si, TiN, and Cu films and concludes that the film‐growth mechanism is independent of the type of substrate. This work is particularly important for many industrial applications, which require unifying a single film deposition process for multiple structural materials. The first results obtained with mechanical Si test structures clearly show that surface amination at room temperature, in open air, and aqueous medium using DIAP can be easily integrated into the fabrication of microelectromechanical systems and, therefore, can potentially replace the currently industrialized organic‐based silanization process.

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 score0.007
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 head0.008
GPT teacher head0.256
Teacher spread0.249 · 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