Executive Summary
Incorporated in everything from automated drones to the device in your pocket, advanced microelectronics are integral to American economic power and military capacity. Their production depends on a complex network of global supply chains operating at a dizzying scale. Despite its intricacy, policymakers must understand the vulnerabilities and competition at play in this global trade system to ensure national security.
But which microelectronics components are most at risk of trade disruption? How would removing one highly connected exporter affect the global supply chain, and which are most influential? What would a simulated attack on the microelectronics export network look like, and how could we model the possible effects?
To address these questions, NSPDI researchers crafted this report building on the data extraction methods for microelectronics supply chains used in our earlier April 2025 product. In this new paper, we use machine learning tools to more deeply analyze the underlying structures of global microelectronics trade flows, creating tools and visualizations to help analysts and policymakers evaluate the resilience of the system and identify emergent risks. Using these models, analysts can quickly grasp trade dynamics across multiple microelectronics materials and point to critical actors and regions in the trade networks.
Key Takeaways
- Microelectronic trade networks are strongly centralized and often hierarchical, implying that many advanced microelectronics precursor materials flow through a central processing or manufacturing point (China’s dominance over rare earths exports is a good example).
- The resilience simulations we ran indicate that trade flows are quite vulnerable to losing the most highly connected countries. For many key materials, just removing the top 10% of trading countries is enough to fragment the entire network.
- Because trade network vulnerability to disruption shifts based on short- and long-term trends, identifying the cause of any fluctuations can point to policy tools that can increase systemic stability.