Engineering Entropy for AI Silicon

COEFFICI

Coeffici integrates microfluidics, magnetocaloric layers, and field-aware software to extend AI compute density beyond conventional thermal limits.

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The Scaling Problem

AI heat flux is exceeding microfluidic hydraulic efficiency limits. Conventional liquid cooling increases flow rate and pressure drop, which is energy intensive and unsustainable at scale.

Fluid-Only Scaling Breaks

Conventional liquid cooling pushes flow rate and pressure drop to chase heat flux. The result is hydraulic inefficiency and rising energy cost.

Thermal scaling must evolve beyond fluid-only optimization.

Our Hybrid Architecture

Microchannels extract heat. Magnetocaloric layers absorb transient entropy spikes. Active field modulation stabilizes thermal response. Software orchestrates the system.

We are not a cold plate vendor. We are not a traditional magnetic refrigeration company. We build thermodynamic architecture.

Core Technology

Four coupled layers engineered to make entropy as designable as fluid flow.

Hardware Layer

Precision microchannel geometry engineered for hotspot targeting and low pressure drop.

Entropy Layer

Low-hysteresis, room-temperature magnetocaloric materials embedded as dynamic entropy buffers.

Field Layer

Low-field magnetic architecture designed for integration feasibility and EMI safety.

Software Layer

Magneto-thermal co-design platform optimizing entropy change, flux distribution, and thermal impedance.

Scientific Foundation

We lead magneto-thermal modeling, entropy-field coupling research, and experimental validation with a focus on low-field feasibility and manufacturable integration.

  • Entropy-field coupling modeled and validated against experimental data
  • Low-field feasibility verified with EMI-safe architectures
  • Hysteresis and cycling durability characterized at room temperature
  • Transient hotspot mitigation correlated from model to silicon

Software Platform

A magneto-thermal co-design engine that models entropy, field dynamics, and hydraulic behavior. This is thermodynamic orchestration software, not monitoring.

Models magnetic flux density and entropy change (ΔS) at chip scale
Captures hysteresis losses, cycling durability, and field-material coupling
Optimizes transient hotspot mitigation and pressure-flow balance

Vision

AI scaling will not be limited by transistors. It will be limited by thermodynamics. Coeffici builds the entropy infrastructure for next-generation compute.

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