Thermal Interface Materials (TIMs) Heat Dissipation in Scaling AI Infrastructure
- David Rogers
- AI Buildout Supply Chain
- 2026-08-14
NEED TO KNOW
- Critical Thermal Function: Thermal interface materials (TIMs) fill microscopic surface voids between high-power dies, spreaders, and cold plates to eliminate air gaps, preventing thermal throttling in high-power (>1 kW) GPUs, ASICs, and HBM stacks.
- Core Material Families: Modern packaging relies on polymer composites (silicone loaded with BN, alumina, or CNTs for 10 W/m·K conductivity) and metallic/liquid-metal alloys (Ga-In-Sn and indium solders offering 50–80+ W/m·K).
- Reliability Bottlenecks: AI workloads present key mechanical failure modes, including liquid-metal pump-out, galvanic corrosion on aluminum, filler-induced viscosity limits in polymers, and die contact loss from 2.5D/3D package warpage.
- Process Innovations: Emerging solutions center on liquid-metal embedded elastomers (LMEE), vertically aligned carbon nanotubes/graphene, vacuum-assisted reflow to eliminate solder voids, and direct-to-die lidless TIM1.5 architectures.
- Market Growth Drivers: Driven by direct-to-chip liquid cooling and rising rack densities, the specialized AI TIM market is expanding rapidly from ~2.5 billion in 2025 toward 5.6 billion by 2034.
- Supply Chain Risks: Primary inputs face severe geographic concentration, with China controlling ~98–99% of primary low-purity gallium production alongside significant indium refining, making recycling and supply diversification strategic priorities.
Thermal interface materials (TIMs) form the necessary bridge that transfers heat from AI processors, high-bandwidth memory (HBM) stacks, and high-power packages to heat spreaders, lids, or cold plates. Without high-performance TIMs, the high power densities of modern GPUs and ASICs which exceed hundreds of watts per chip and approach 1 kW, would cause thermal throttling or system failure /Nature Electronics/.
High-performance TIMs use two main material types. Polymer-based greases, gels, pads, and phase-change materials use pure silicone or other base polymers mixed with high amounts of thermally conductive fillers, such as boron nitride, alumina, silver flake, graphite, or carbon nanotubes. Manufacturing requires precise control of particle sizes, surface treatment of inert fillers to prevent clumping, and low ionic contamination levels to protect semiconductor packages from failure. Metal and liquid-metal TIMs (gallium-indium-tin alloys or indium solders) require high-purity gallium and indium. These materials provide bond-line thicknesses below 50 µm, thermal conductivities from ~10 W/m·K for advanced polymers to 50–80+ W/m·K for metals, and good conformability to warped packages through thousands of thermal cycles /IEEE/.
Key reliability challenges under heavy AI workloads include liquid-metal pump-out, galvanic corrosion (especially with aluminum), and metal migration. Polymer systems face limits on filler loading, which increases viscosity and makes processing difficult, along with interface phonon scattering and long-term material degradation or void formation /European Polymer Journal/. Package warpage in 2.5D/3D packages and HBM stacks further reduces surface contact. Emerging production methods aim to reduce cost, waste, and processing time. These include polymer-encapsulated liquid-metal composites for better flexibility and containment, aligned carbon-nanotube or graphene networks, surface-treated boron nitride for better mixing, vacuum-assisted or pressure-controlled reflow to reduce solder voids, and automated precision dispensing for high-volume assembly. These methods also enable lidless TIM1.5 designs that remove intermediate thermal interfaces.
Demand continues to grow in AI data-center GPUs and accelerators (the largest market segment), HBM packaging, server circuit boards, and liquid-cooled cold plates. Industry estimates valued the specialized AI TIM market at roughly $2.5 billion in 2025 and project it to reach $5.6 billion by 2034 /Fortune Business Insights/, with faster growth in the HBM-TIM segment. The average TIM value per AI server rack has increased significantly as premium materials replace standard greases. Higher thermal design power, denser packaging, and the adoption of direct-to-chip and immersion cooling drive this transition.
Rapid AI market growth strains current TIM supply chains. Major industry suppliers include Henkel (BERGQUIST/LOCTITE product lines), Shin-Etsu (silicone greases), Dow, Indium Corporation (metal and liquid-metal products), Fujipoly, Parker Hannifin/Chomerics, Honeywell, and specialist companies such as Arieca (liquid-metal composites). The geographic supply concentration, specifically Chinese control of gallium and indium refining, along with Japanese production of high-purity inputs, creates supply risks that users and governments are trying to reduce through supplier diversification and recycling initiatives. Overall, TIMs are a critical strategic input rather than a standard commodity. Their chemical purity, processing accuracy, and supply chain security directly affect how quickly operators can scale AI computing infrastructure.
Key Insights
What volume of TIM is required per server rack for next-generation platforms like NVIDIA’s Vera Rubin NVL72 or AMD’s Helios, and how does this change the bill of materials (BOM)?
Rack-scale architectures like NVIDIA’s Vera Rubin NVL72 (housing 72 Rubin GPUs and 36 Vera CPUs) and AMD’s Helios (housing 72 Instinct MI450-series GPUs) push rack power envelopes well beyond 100 kW. At these extreme heat fluxes, conventional thermal greases applied at milligram scales are structurally insufficient. A single NVL72 or Helios rack consumes approximately 1.5 to 2.5 kilograms of high-performance TIMs—spanning metallic phase-change materials (PCMs) or liquid-metal composites for TIM1/TIM1.5 die-to-cold-plate interfaces, alongside ultra-high-density gap fillers for power delivery modules, network switches, and HBM4 stacks. While traditional thermal grease accounts for under 20 in a standard enterprise server, the transition to high-conductivity, highly compliant metallic and polymer-matrix TIMs escalates the thermal BOM to 1,500–$3,500 per AI rack, transforming thermal interface materials into a high-value core component of rack-scale liquid-cooling infrastructure.
What is the most critical bottleneck process technology in scaling next-generation TIM production for high-density AI accelerators?
The paramount manufacturing bottleneck is achieving sub-50 µm bond-line thickness (BLT) with zero voiding (<1%) over large-area, severely warped 2.5D/3D semiconductor dies without inducing mechanical pump-out or material degradation under cyclic thermal stress. For polymer-matrix TIMs, increasing thermally conductive filler loading (such as surface-functionalized boron nitride or graphene) to exceed 10 W/m·K causes exponential viscosity spikes, making standard automated dispensing non-viable and raising mechanical pressure requirements during package assembly. For solder and liquid-metal alternatives, the bottleneck centers on precise vacuum-assisted reflow processing and micro-encapsulation containment (e.g., liquid-metal embedded elastomers) to prevent liquid-phase migration, galvanic corrosion on aluminum cold plates, and short circuits across ultra-dense micro-bump arrays during thousands of dynamic thermal cycles.
What are the unit economics, margin defensibility, and supply contract dynamics for specialized AI TIM manufacturers?
Specialized TIM suppliers command premium gross margins ranging from 55% to over 70%—significantly higher than commodity silicone packaging—because their products require complex synthetic chemistry, high-purity inorganic refinement (such as 6N gallium and indium), and custom formulation IP. Due to strict qualification cycles where a TIM failure can trigger the thermal throttling or physical destruction of a $40,000+ AI accelerator die, hyperscalers and tier-1 chipmakers lock in 3-to-5-year long-term supply agreements (LTSAs) that ensure strict pricing power and high customer stickiness. Although the broader semiconductor capital cycle exhibits inherent cyclicality, TIM revenues remain highly defensible and structurally growth-oriented because thermal design power (TDP) per chip escalates across every successive architectural node, driving continuous ASP expansion as systems migrate from standard greases to custom phase-change and liquid-metal composite formulations.