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<p>As artificial intelligence (AI) chips become more powerful, the thermal management capabilities of conventional silicon (Si) substrates become insufficient for 3D-stacked designs. This work integrates electrically insulative and thermally conductive hexagonal boron nitride (h-BN) interposers into AI chips for effective thermal management. Using COMSOL Multiphysics, the effects of High-Bandwidth Memory (HBM) distributions and thermal interface material configurations on heat dissipation and hotspot mitigation were studied. A 20&#xa0;K reduction in hot spots was achieved using h-BN interposers compared to Si interposers. Such an improvement could reduce AI chips' power leakage by 22% and significantly enhance their thermal performance.</p> Graphical abstract <p></p>

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Thermal analysis of 3D GPU-memory architectures with boron nitride interposer

  • 期刊论文

  • 发表日期：

    2026年1月12日

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  • Eric Han Wang,
  • Weijia Yan,
  • Ruihong Huang

摘要

As artificial intelligence (AI) chips become more powerful, the thermal management capabilities of conventional silicon (Si) substrates become insufficient for 3D-stacked designs. This work integrates electrically insulative and thermally conductive hexagonal boron nitride (h-BN) interposers into AI chips for effective thermal management. Using COMSOL Multiphysics, the effects of High-Bandwidth Memory (HBM) distributions and thermal interface material configurations on heat dissipation and hotspot mitigation were studied. A 20 K reduction in hot spots was achieved using h-BN interposers compared to Si interposers. Such an improvement could reduce AI chips' power leakage by 22% and significantly enhance their thermal performance.

Graphical abstract