With single-card power of AI chips like NVIDIA GB300 and Huawei Ascend 910B surpassing 1.2 kW, traditional air cooling has reached its physical limits. Between 2025–2026, global data centers are rapidly shifting to immersion liquid cooling. As the direct-contact coolant, silicone oil is no longer a standard industrial product but a high-performance “electronic-grade functional fluid.”
Unlike conventional heat transfer oils, silicone oil for AI liquid cooling must meet four stringent requirements simultaneously: high insulation, ultra-low viscosity, low-temperature fluidity, and intrinsic safety. Industry consensus is forming new benchmarks:
Dielectric strength >30 kV/2.5 mm, ensuring no breakdown under dense GPU/CPU arrangements;
Kinematic viscosity <5 cSt (25°C) to reduce pumping energy and enhance convective heat transfer;
Pour point ≤ –50°C to prevent solidification in cold or startup conditions;
Flash point >180°C, non-corrosive, excellent material compatibility to avoid PCB, seal, or connector damage over time.
“Reducing viscosity by 1 cSt can lower system circulation power by 3%–5%,” said a liquid cooling solution engineer. “Too low viscosity may increase evaporation, so molecular design must achieve precise balance.”
Mainstream choices are high-purity linear methyl silicone oil or lightly phenyl-modified silicone oil, with deep distillation reducing D4/D5 cyclic impurities below 10 ppm to avoid high-temperature deposition on chips. Leading suppliers now offer “low-viscosity, high-flash” silicone oils optimized for AI clusters. Tests on the NVIDIA GH200 platform show GPU hotspot temperatures drop 8–12°C compared to mineral oil, without degrading signal integrity.
Not all “insulating oils” are suitable. Transformer oils have high viscosity and flammability, while fluorinated fluids are costly and environmentally controversial. Compliant silicone oils achieve the best balance of safety, energy efficiency, and cost.
As large-scale AI clusters expand, liquid-cooling silicone oil is evolving from an “auxiliary material” to a “critical component of computing infrastructure.” Suppliers who can deliver ppm-level purity and cSt-level precision hold the key to enabling green data centers in the AI era.
