F E A T U R E
manufacturing cannot easily achieve, allowing coolant to be guided through complex geometries with far greater control. The result is a cold plate capable of achieving both exceptionally low thermal resistance and very low pressure drop – two characteristics that are often difficult to optimise simultaneously.
The manufacturing process also improves reliability. Rather than assembling multiple machined layers together, additive manufacturing enables cold plates to be produced as single monolithic components. Removing bonded interfaces significantly reduces potential leak paths while improving structural integrity, an important consideration in facilities where even brief interruptions can have significant operational and financial consequences.
It is a principle well established in Formula One engineering, where monolithic components are widely used to improve reliability by eliminating joints while withstanding extreme thermal and mechanical loads.
Engineering that evolves as quickly as technology
Perhaps the biggest lesson Formula One offers AI infrastructure is not simply how to engineer better cooling systems, it’ s how to engineer them faster.
Traditional manufacturing relies on tooling, multiple production stages and assembled components, making design changes slower and more expensive. Because additive manufacturing produces components directly from digital models, engineers can rapidly adapt internal flow paths, channel geometries and mounting configurations without redesigning production tooling. Cooling solutions can therefore evolve alongside successive processor generations rather than constraining them.
Rapid iteration also depends on being able to validate performance just as quickly. At Conflux, in-house calorimetric testing allows single-phase cold plate designs to be thermally characterised and verified within days rather than weeks, while rack-scale testing capability enables system-level design verification under representative data-centre operating conditions.
By combining design, manufacture and performance testing under one roof, engineers can rapidly refine designs using real-world performance data, significantly accelerating development cycles.
For organisations deploying AI infrastructure, that agility is becoming almost as valuable as absolute thermal performance.
Engineering for an industry that never stands still
At first glance, Formula One and AI infrastructure appear to be worlds apart, yet the parallels are striking once you spot them. Both operate on relentless development cycles, where every new generation of technology demands a corresponding evolution in the systems around it. In both, thermal management is crucial.
For data centres, liquid cooling will become the standard, but competitive advantage will depend on how efficiently it is engineered. As processor power continues to climb, systems that balance heat removal, pressure drop, reliability and deployment speed will be better placed to reduce operating cost, improve flexibility and support long-term performance.
Perhaps Formula One’ s greatest lesson is that thermal management is never a finished problem. It is an engineering discipline built on continuous optimisation, rapid iteration and the ability to adapt as technology evolves.
Fortunately, engineers have always performed best when the heat is on. �
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