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Record W4416876030 · doi:10.37665/smdadtm75143

Enhancing Thermal Fatigue Reliability of Pb-Free Solder Alloys with Additions of Bismuth and Antimony

2020· article· W4416876030 on OpenAlex
Richard Coyle, Charmaine Johnson, Dave Hillman, T. J. Pearson, Michael Osterman, Joe Smetana, Keith Howell, Hongwen Zhang, Julie Silk, Jie Geng, Derek Daily, Babak Arfaei, Ranjit Pandher, André M. Delhaise, Stuart Longgood, Andre Kleyner

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

VenueSMTA International · 2020
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsHain Celestial (Canada)Alpha Technologies (Canada)
Fundersnot available
KeywordsBall grid arraySolderingTemperature cyclingBismuthReliability (semiconductor)AntimonyAlloy

Abstract

fetched live from OpenAlex

ABSTRACT The thermal fatigue reliability of multiple high reliability solder alloys containing significant additions and combinations of bismuth (Bi) and antimony (Sb) are compared to alloys with additions of Bi or Sb only. The study uses daisy chained test vehicle that includes a 192-pin chip array ball grid array (192CABGA) and an 84-pin thin core BGA (84CTBGA). Thermal cycling is done in accordance with the IPC-9701 attachment reliability guideline using three distinct thermal cycling profiles, 0/100°C, -40/125°C, and -55/125°C. The results indicate that combinations of Bi and Sb generally are more effective than either element as a single alloying addition, although the reliability margins in thermal cycling tests are not always great. The differences in alloy performance with the two BGA packages are compared using Weibull statistics, microstructural characterization, and failure mode analysis.

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 score0.069
Threshold uncertainty score0.894

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 science0.0010.000
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 head0.015
GPT teacher head0.225
Teacher spread0.209 · 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