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Study of Immersion Tin Plating on Copper by Galvanic Couple Current Method

2010· article· en· W2156261648 on OpenAlexaff
Xue Hua Liu, Dian Tang, Shi Wen

Bibliographic record

VenueAdvanced materials research · 2010
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsMcGill University
FundersNational Natural Science Foundation of China
KeywordsGalvanic cellImmersion (mathematics)Materials scienceGalvanic anodeCopperThioureaMetallurgyElectrochemistryPlating (geology)TinScanning electron microscopeCurrent densityComposite materialCathodic protectionChemistryElectrode

Abstract

fetched live from OpenAlex

Immersion tin (I-Sn) coatings on copper were prepared in a stannous methanesulfonate bath with thiourea being the potential altering agent. The electrochemical displacement process was studied by the galvanic couple current method (GCCM) on an electrochemical workstation. The morphology of the I-Sn coatings were observed by field-emission-gun scanning electron microscopy (FEG-SEM). The I-Sn process can be divided into three stages: (i) rapid increase in galvanic current, (ii) sudden decrease in galvanic current after a peak current, and (iii) low or residual galvanic current stages. It is demonstrated that the galvanic current method is a useful and efficient tool to identify the optimum ending time of the immersion plating process. This optimum immersion time results in a smooth and conformal deposit with a fine grain size.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.045
GPT teacher head0.401
Teacher spread0.356 · 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

Citations6
Published2010
Admission routes1
Has abstractyes

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