MagFlux is pioneering solid-state thermal management for Exascale AI. By replacing mechanical cooling with zero-moving-part Magnetohydrodynamic (MHD) pumps and regenerative liquid-metal loops, we are eliminating the thermal bottlenecks of next-generation GPU clusters and defining the standard for Sustainable AI Factories.
Traditional cooling infrastructure cannot scale to meet the extreme TDP demands of next-generation AI accelerators. MagFlux is an advanced engineering initiative solving this crisis. We design integrated, high-efficiency electromagnetics and liquid-metal MHD loops that remove immense heat fluxes with zero moving parts — modeled, iterated, and validated natively on NVIDIA infrastructure before physical prototyping.
High-torque-density motor topologies optimized for air-gap flux density and minimized iron losses.
Self-shielding permanent magnet arrangements that maximize flux on one side for linear and rotary applications.
Finite element analysis pipelines integrated with our AI research agents for rapid design-space exploration.
Characterization of soft magnetic composites, amorphous metals, and rare-earth magnet grades for target configurations.
Leveraging NVIDIA Omniverse to build high-fidelity digital twins of liquid-metal thermal loops. We simulate extreme thermal fluxes and stress-test exascale cooling loads in physically accurate environments.
MagFlux leverages cutting-edge artificial intelligence to rapidly accelerate the research and development pipeline. Our proprietary multi-agent workflows drastically reduce iteration time from conceptual physics to robust finite element models.
Utilizing large language models and optimized design agents running on dedicated NVIDIA GPU infrastructure, we power a continuous research pipeline. This enables autonomous literature ingestion, complex equation derivation, parametric sweep generation, and advanced design-space optimization tailored specifically for complex electromagnetic architectures.