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Effects of Microstructure on Material Behaviors of Solder Alloys

2005· article· en· W1965581164 on OpenAlexaff
Tae Kyung Hwang, Soon Bok Lee

Bibliographic record

VenueKey engineering materials · 2005
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsMaterials scienceMicrostructureEutectic systemUltimate tensile strengthSolderingTensile testingMetallurgyNanoindentationCastingSupercoolingComposite material

Abstract

fetched live from OpenAlex

The leading candidates for replacing lead-contained solders are near ternary eutectic Sn/Ag/Cu alloys. The electronic industry has begun to study both the process behavior and the reliability assessment of these alloys in detail to figure out their applicability to electronic devices and products. In recent publications, the solidification behavior and the fatigue life of the accelerated thermal cycle test have been reported in terms of microstructure variations such as the formation of large Ag3Sn plates and their effects. In this study, coupon type bulk specimens have been made for uniaxial tensile test by casting. To consider the effects of microstructure, casting cooling rates were controlled to 0.02-2.0 oC/sec. Eutectic Sn/Pb and near eutectic lead-free solder materials – Sn/Ag/Cu and Sn/Cu alloys – were used in mechanical testing. Also, nanoindentation tests were performed to measure Young’s modulus of materials having different microstructures. Tensile tests were performed at 3 different strain rates and then acquired 0.2% offset proof stress, ultimate tensile strength and elongation to failure.

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 score0.001
Threshold uncertainty score0.003

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 science0.0000.000
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 head0.003
GPT teacher head0.179
Teacher spread0.176 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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