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Record W2030406323 · doi:10.1149/2.0051506eel

Galvanic Deposition of Silver on Silicon Surfaces from Fluoride Free Aqueous Solutions

2015· article· en· W2030406323 on OpenAlexafffund
S. S. Djoki, Ken Cadien

Bibliographic record

VenueECS Electrochemistry Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsGalvanic cellDeposition (geology)SiliconAqueous solutionFluorideMaterials scienceSingle displacement reactionInorganic chemistryIonChemical engineeringMetallurgyChemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Direct deposition of silver from fluoride-free alkaline solutions containing Ag(I) ions at pH higher than 12 onto silicon surfaces at room or elevated temperatures has been demonstrated. This deposition does not require a reducing agent, i.e. process proceeds via galvanic displacement reactions. This new process that is based on strong alkaline and fluoride-free solutions was experimentally illustrated through XRD and SEM analyses. Theoretically, it was confirmed that this process is thermodynamically favorable at room temperature, however for the real industrial applications elevated temperatures (up to 100°C) are recommended.

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 score0.026
Threshold uncertainty score0.710

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 head0.180
Teacher spread0.173 · 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

Citations12
Published2015
Admission routes2
Has abstractyes

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