Research on Electrochemical Migration Failure Behavior of Automobile Circuit Board
Bibliographic record
Abstract
In this paper, the electrochemical migration experiments of circuit boards with different electrodes size and spacing were investigated under different voltage bias by water drop method experiments. Furthermore, based on standard size spacing specimens, experiments of specific voltage bias were conducted under the influence of different chloride ion concentration and adipic acid concentration. Thus, the electrochemical migration failure behavior of automobile circuit boards is deeply explored, providing a basis for improving the reliability of automotive electronic products.It is concluded that bias voltage is the driving force for electrochemical migration, and smaller spacing and larger electrode size increase the probability of metal ions in the dielectric reaching the cathode surface. The increase in chloride ion concentration leads to an increase in the inter electrode current, followed by a large amount of precipitation between the electrodes, resulting in an increase in the resistivity of the entire solution. Therefore, the inter electrode current decreases to a stable value, further increasing the probability of electrochemical migration. However, low concentrations of chloride ions do not participate in the formation of precipitation and dendrite growth. When the concentration of chloride ions is high, chloride ions further promote electrochemical migration by dissolving tin hydroxides. The impact mechanisms of adipic acid and sodium chloride on electrochemical migration are different. The acid ions generated by the ionization of adipic acid will react with tin ions in the solution, hindering the diffusion of tin ions and thus delaying the initiation and growth of dendrites.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".