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High Throughput Microfluidic Rapid and Low Cost Prototyping Packaging Methods
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多尺度模拟在先进的电子包装中的应用.

Wei Yu1, Shucan Cheng1, Zeyuan Li2

  • 1School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China.

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概括

本综述探讨了电子包装中的多物理合,这对于设备性能和可靠性至关重要. 它强调了先进的多尺度模拟技术,包括机器学习,用于增强电子系统设计和保护.

关键词:
先进的电子包装,先进的电子包装电子设备 电子设备 电子设备机器学习方法 机器学习方法多个尺度的模拟.多物理合器

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科学领域:

  • 电子工程 电子工程 电子工程
  • 材料科学是一种材料科学.
  • 计算物理学的计算物理.

背景情况:

  • 电子包装可以保护设备免受环境因素的影响.
  • 包装设计涉及复杂的多物理现象,如热传输和机械应力.
  • 评估电子设备的性能和可靠性需要了解多物理合.

研究的目的:

  • 提供电子包装中的多物理合的全面概述.
  • 总结一下电子包装多尺度模拟技术的最新进展.
  • 为了说明这些方法在研究电子包装方面的应用.

主要方法:

  • 复习多尺度模拟技术:有限元素方法 (FEM),分子动力学 (MD),密度函数理论 (DFT).
  • 专注于机器学习 (ML) 方法,以弥合不同的模拟尺度.
  • 在材料特性,接口故障,热管理,电迁移和应力分析方面的应用例子.

主要成果:

  • 多尺度模拟对于分析复杂的电子包装现象至关重要.
  • 机器学习在整合宏观和微观模拟尺度方面显示出前景.
  • 这些技术可以详细研究关键的电子包装问题.

结论:

  • 多尺度模拟技术为推进电子包装设计和可靠性提供了巨大的潜力.
  • 确定了应用这些方法的挑战和未来的研究方向.
  • 建议对电子包装进行进一步的ML驱动的多尺度模拟研究.