The global computing industry's pursuit of AI breakthroughs is hitting a "thermal wall." That phrase comes directly from a team at the Chinese Academy of Sciences, and they are not being dramatic. Every watt pushed through a GPU die has to go somewhere. The path from silicon to heat sink is governed by a thin layer of thermal interface material, and that layer is now the bottleneck holding back the entire AI hardware stack. A functional carbon materials team at the Ningbo Institute of Industrial Technology, part of CAS, has responded with a diamond-copper composite coating that improved cooling efficiency by 80% when deployed at an AI computing node in Zhengzhou, Henan province. The composite also delivered a 10% improvement in chip performance. Numbers like that demand both scrutiny and a serious look at what this team actually built.
Thermal interface materials sit in the most consequential gap in data center hardware. Between the chip die and the cold plate (or heat sink), there is a microscopic space riddled with surface imperfections, air pockets, voids, and tiny canyons of thermal resistance that throttle heat transfer before it even begins. TIMs exist to fill that gap with something that conducts heat far better than air, which manages roughly 0.025 W/mK. Traditional TIMs, the thermal pastes and pads used across commercial servers, typically deliver thermal conductivity in the range of 1 to 10 W/mK. Good enough for 200W chips. Increasingly inadequate as NVIDIA's watt roadmap pushes single-GPU thermal design power past 1,000 watts.
The physics are plain. Higher heat flux at the die surface demands lower thermal resistance at every layer in the conduction path. The TIM layer, because it is so thin and sits at the most critical junction, contributes a disproportionate share of total thermal resistance. Improve the TIM, and you lower junction temperatures across the board. Lower junction temperatures mean the chip runs faster at the same power, or the same speed with less cooling overhead. That is where the 10% chip performance gain comes from.
Diamond is the highest thermal conductor found in nature. Single-crystal diamond conducts heat at roughly 2,200 W/mK, four to five times better than copper's 400 W/mK. But diamond is brittle. It does not conform to surfaces, cannot be spread like a paste, cannot be stamped into a compliant pad. Used alone, diamond makes a terrible interface material because the contact area is too small to transfer heat effectively.
The CAS team's approach combines diamond with copper in a composite structure where copper supplies the ductility and machinability while diamond carries the thermal load at speeds no metal can match. The resulting composite achieves thermal conductivity exceeding 1,000 W/mK. A hundred times better than conventional thermal paste. More than double pure copper. The engineering challenge is the interface between diamond particles and the copper matrix, because poor bonding at that boundary creates thermal resistance that erases diamond's advantage entirely. The Ningbo team appears to have solved this with a coating process that ensures strong metallurgical bonding between the two phases.
Research groups in Japan, Germany, and the United States have been working on similar diamond-metal composites for over a decade, primarily for aerospace and power electronics applications. What makes the CAS result different is deployment. They put it in an actual AI computing node and measured real performance. Lab results on thermal conductivity samples are one thing. An 80% cooling efficiency improvement on a working AI server, measured in a production environment in Zhengzhou, is a fundamentally different kind of evidence.
China currently depends on imported heat dissipation materials for its data center infrastructure. Honeywell, Shin-Etsu, Dow, Parker Hannifin. The high-end TIM market belongs to companies in the U.S., Japan, and Europe, and these firms supply the thermal pastes, phase-change materials, and metallic TIMs that go between chip and cold plate in servers worldwide.
That dependency is a vulnerability. Export controls have already restricted Chinese access to advanced GPUs. Chinese universities have been cut off from NVIDIA and Supermicro hardware. Huawei is building its own AI accelerators and needs domestic thermal solutions. Google has been tapping Chinese liquid cooling suppliers even as the broader technology relationship fractures. The thermal interface layer is one more component where China does not want to depend on foreign suppliers who might disappear overnight.
Developing a domestic diamond-copper composite TIM with 1,000+ W/mK conductivity is a strategic investment. Full stop. If China can manufacture this material at data center scale, it removes one more dependency from the supply chain feeding its AI buildout.
A better TIM does not replace direct-to-chip liquid cooling. It makes liquid cooling work better. The conduction path from die to coolant runs through the TIM, through the integrated heat spreader (if present), through the cold plate, and into the liquid loop. Improving the TIM reduces the first thermal bottleneck in that chain, which means the liquid cooling system can extract more heat per degree of temperature difference. Complementary technologies.
The same logic applies to microfluidic cooling approaches being pursued by Microsoft and others. Even when coolant channels are etched directly into the chip package, there is still a material interface between the channel walls and the die. Better materials at that boundary improve the entire system.
The TIM market itself is projected to grow alongside the AI infrastructure buildout. Every new GPU rack needs thermal interface materials, and every generation of higher-power chips needs better ones. The volumes are not enormous by commodity materials standards, but the margins are high and the switching costs are real because once a data center operator qualifies a TIM for use with a specific GPU and cooling system, they tend to stick with it for years. Getting designed into that stack early is worth a lot.
The CAS diamond-copper composite is a real result with real deployment data. An 80% cooling efficiency improvement on a working AI node is a proof point. Whether it scales to volume manufacturing at costs competitive with existing TIMs is the open question, and the only one that matters.
Our read: the material science works. Diamond-copper composites at 1,000+ W/mK are physically real and the metallurgy is well understood. The harder problem is production, which means synthesizing diamond particles, controlling grain size and distribution, achieving consistent bonding with the copper matrix, and doing all of this at a price that data center operators will actually pay. That manufacturing challenge is where Chinese industrial policy has historically been effective. State-backed research institutes develop materials, state-backed manufacturers scale them, and the rest of the world watches the cost curve fall.
Within three years, expect domestically produced high-conductivity TIMs to appear in Chinese-manufactured AI servers from Huawei, Inspur, and Sugon. The foreign TIM suppliers who currently serve that market will lose share. The rest of the industry will face a new competitive dynamic: Chinese AI infrastructure running on thermal materials that Western data centers cannot buy, delivering cooling performance that closes part of the gap created by chip export controls. The thermal wall is real. China just found a different way to push through it.