As AI infrastructure migrates to 800 V distribution and humanoid robots embed power electronics directly within joints, Generation 7 GaN and integrated GaN ICs are enabling higher efficiency, faster switching and dramatically improved power density in the critical 15 V to 40 V range — reshaping how hardware development teams approach next-generation conversion architectures.
As artificial intelligence infrastructure scales toward megawatt-class racks and 800 V distribution architectures, and humanoid robotics pushes power electronics directly into joints and actuators, the demands placed on conversion efficiency, density and dynamic performance have fundamentally shifted. Traditional silicon MOSFET-based designs are increasingly constrained by switching losses, thermal limits and physical footprint — particularly in the 15 V to 40 V range that underpins motor drives, point-of-load converters and distributed robotics power stages.
Against this backdrop, Efficient Power Conversion (EPC) is positioning its Generation 7 GaN platform as a step change in low-voltage power performance. Showcased at Applied Power Electronics Conference (APEC) 2026, the latest eGaN devices and integrated GaN ICs are designed to move beyond evaluation boards and demonstration platforms toward production-ready architectures for AI computing and next-generation robotics. By combining lower RDS(on), reduced gate charge and faster switching capability, Gen 7 aims to outperform silicon MOSFETs across key efficiency and power density metrics, while enabling tighter integration and simplified layouts.
For hardware development engineers, however, performance claims are only part of the equation. The practical realities of parasitic management, EMI control, thermal modelling in sealed joints, high di/dt layout discipline and long-term reliability under aggressive load transients ultimately determine whether GaN can be deployed at scale.
In the following Q&A, we explore the device-level innovations behind Gen 7 GaN, the system-level implications for AI rack power delivery and embedded robotic motor drives, and the critical design considerations for teams transitioning from silicon to high-frequency, high-density GaN architectures.
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