As copper block embedding technology continues to be applied in printed circuit board (PCB) products, the materials used in PCBs vary, resulting in significant differences in their coefficients of thermal expansion (CTE).
After embedding copper blocks into PCBs and subjecting them to four lead-free reflow soldering cycles, the resin in the PCB material contracts.
Simultaneously, the tensile stress generated by this resin contraction causes cracks to form at the interface between the resin and the copper blocks.
Customers reject this cracking phenomenon. To prevent this issue, material optimization and process parameter adjustments were employed to mitigate cracking.
This article focuses on key points and monitoring aspects for improving PCB copper-embedded block cracking.
1 Control Guidelines for Copper-Embedded Block Cracking Defects
Specific settings for prepreg resin content (RC) and compression parameters are detailed below.
(1) Adjust the resin content (RC) value of the prepreg (PP). Replace low-resin-content PP with medium-to-high-resin-content PP, with a recommended 2% increase in resin content from the original level.
(2) Adjust lamination parameters:
Pressure: 450 psi
Transition to high-pressure temperature: 90°C
Heating rate: 3.15°C/min curing time: 125 min.
2 Improvement Measures for Copper-Embedded Block Cracking
Establish key process parameter control measures for this PCB type, as shown in Table 1.
3 Effectiveness of Crack Improvement Measures
Implementing these improvement strategies and control plans effectively mitigated cracking defects between copper-embedded blocks and resin.
Post-improvement, scrap rate decreased from 50% to 5%. The pre- and post-improvement effects are shown in Figure 1.
4 Conclusion
Implementing the process control plan for PCB buried copper blocks as described above ensures resolution of crack issues in these products.
This approach meets customer requirements and guarantees no abnormalities during client production.
However, since different PCB material types exhibit variations, control measures must be adjusted and optimized based on actual conditions.