Impact of Higher Melting Lead-Free Solders on the Reliability of Printed Wiring Assemblies
Bibliographic record
Abstract
ABSTRACT The move toward lead-free electronics has become a rapidly emerging issue for concern and evaluation. The movement has been triggered by the European Union's (EU) proposal for a Directive on Waste from Electrical and Electronic Equipment (WEEE) and by the Japanese focus on environmental marketing. The candidate solder alloys that have been identified as substitutes require high soldering temperatures since these alloys have typical melting temperatures between 198°C and 227°C. Concern has been raised that the higher processing temperatures required for wave and reflow soldering with these alloys will create increased drop out due to printed wiring board (PWB) warpage and component failures, since most components are not qualified in terms of reliability for these higher processing temperatures. In this paper, we present evidence for an additional reliability concern for lead-free soldered electronic product. Conductive anodic filament (CAF) formation is a failure mode associated with boards, which either operate or are stored in a humid environment. This paper compares the number of CAF formed on boards reflowed at 201°C vs. 241°C after aging under 100V bias at 85°C/85% RH for 28 days. The incidence of CAF under the higher reflow conditions was typically 1-2 orders of magnitude greater than at the lower reflow conditions. The data provide additional reliability concerns for lead-free soldering.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".