KAIST Develops Ultra-Efficient Chip Liquid Cooling: Room-Temperature Water Reaches Inside the Chip to Break the AI Cooling Bottleneck

Keywords: Korea Advanced Institute of Science and Technology, chip liquid cooling, AI cooling, microchannel cooling, 3D manifold structure, data centers, thermal management, semiconductor manufacturing

Introduction

As artificial intelligence, large-model training, high-performance computing, and 3D-stacked chips develop rapidly, chip power consumption and heat output are rising at an unprecedented pace. For modern semiconductor systems, performance gains no longer depend only on compute, bandwidth, and packaging. Cooling capability is becoming the key factor that determines the upper limit of the system. Traditional air cooling and external cold-plate cooling are mature, but in high heat-flux scenarios they are increasingly close to physical limits and can no longer meet the needs of next-generation AI hardware.

Recently, a research team at the Korea Advanced Institute of Science and Technology (KAIST) announced an ultra-efficient liquid-cooling technology: room-temperature water is injected directly into ultra-fine channels inside the chip for cooling. According to the results, the cooling performance index is 10 times the previous record, and the research was published on June 15 in the international journal Energy Conversion and Management. More importantly, the technology not only breaks through on performance, but also shows strong application potential in cost, process compatibility, and industrial deployment, potentially offering a brand-new path for thermal management in future high-density compute devices.

1. Chip Heat Is Spiraling, and Traditional Cooling Is Near Its Limit

For decades, electronic cooling has mainly followed the idea of “taking heat away from outside the chip.” Whether using air cooling, heat sinks, or liquid cold plates, the essence is external thermal management. These methods work well in low- to medium-power devices, but their limits become obvious in AI accelerators, data-center servers, power semiconductors, and 3D-stacked chips.

On one hand, transistor density keeps rising, and the heat generated per unit area increases sharply. On the other hand, there are often many layers of material and thermal interfaces between the chip and the cooling medium. Heat must pass through the silicon die, packaging layers, thermal interface materials, and then reach the cooling structure, creating a long thermal-resistance chain with limited efficiency. As a result, even if the external cooling system keeps getting stronger, hot spots inside the chip can continue to build up, causing temperature imbalance, performance throttling, and even reliability issues.

Against this backdrop, researchers have begun to shift their focus from “surface cooling” to “internal cooling.” If the coolant can be brought closer to the heat source, or even act directly inside the chip, cooling efficiency could improve by orders of magnitude. KAIST’s new solution is a major step in that direction.

2. Embedding Cooling Channels Inside the Chip: A 3D Manifold Multi-Channel Microchannel Structure

The core of KAIST’s development is a 3D manifold multi-channel microchannel cooling structure that can be embedded directly inside a silicon chip. Unlike traditional designs that place a cold plate above the chip, this approach builds a fine flow-channel network inside the chip itself, allowing room-temperature water to flow near the heat source through micro-scale channels, enabling much more efficient heat exchange.

The key is the combination of a manifold and microchannels. The manifold distributes the coolant, sending incoming water evenly to each microchannel. The microchannels, thinner than a strand of hair, handle direct heat exchange with the chip’s hot zones. With multiple inlet and outlet points, the whole fluid system behaves like an efficient logistics network: coolant is split, distributed, carried through, and then quickly collected and discharged, avoiding the uneven flow and local blockage that can happen with a single path.

The biggest advantage of this distributed design is that it greatly shortens the flow distance. The shorter the path, the lower the flow resistance and the lower the pumping pressure required. At the same time, coolant is distributed more evenly across the chip, the temperature field is more stable, and hot spots are effectively suppressed. For high heat-flux devices like AI chips, temperature uniformity is often directly linked to lifetime, stability, and frequency headroom, so this design does more than “cool down”; it helps “keep temperatures steady.”

3. Staying Cool Even Under Extreme Heat Flux

According to the team’s disclosed data, even under extreme heat-generation conditions above 2,000 W/cm², the system could keep the chip temperature below 100°C. That is highly significant in practice. In high-end AI chips, GPU clusters, and high-power electronic modules, heat flux is already nearing or exceeding the tolerance boundary of traditional liquid-cooling solutions, and once temperature control fails, system performance drops quickly.

It is also worth noting that the experiment was not performed under an abstract condition, but validated using a 5 mm × 5 mm test chip. Although small, it is enough to demonstrate the structure’s potential efficiency at the micro scale. The team further estimated that when applied to larger AI semiconductor chips (up to 7.5 cm × 7.5 cm) and data-center cold plates, cooling performance could improve by more than 30% versus existing methods. That means the approach is not only suitable for lab verification, but also has a realistic path to engineering deployment.

4. From Performance to Cost: The Industrial Value of Higher COP

Cooling system quality should not be judged only by how much it lowers temperature, but also by how much energy and complexity it requires. The team found that under the same temperature-rise conditions, the system’s coefficient of performance (COP) reached 106,000, about 10 times the result reported by Nature in 2020. The significance is straightforward: to deliver the same cooling power, the required pump power is only about one-tenth of current technology.

This is not just a performance leap, but also a system-level cost optimization. For data centers and high-performance computing platforms, cooling power consumption is far from trivial. If pump power drops significantly, the gains include lower operating costs, better overall energy efficiency, and less long-term maintenance pressure. For AI infrastructure deployed at scale, even a few percentage points of cooling-energy savings can translate into huge economic gains, and this technology pushes the “one-tenth pump power” improvement into a more imaginative range.

At the same time, the approach avoids many expensive and hard-to-scale cooling paths. It does not rely on phase-change cooling, does not require complex nano-surface treatments, and does not need costly special materials such as diamond. In other words, the breakthrough does not come from stacking up materials and manufacturing complexity, but from fundamentally optimizing the structure and fluid-distribution mechanism. Using ordinary room-temperature water as the coolant also lowers the deployment and maintenance threshold, which is especially important for industrialization.

5. CMOS-Compatible Process: A Realistically Deployable Innovation

Many advanced cooling technologies fail to scale not because they are weak, but because their manufacturing process is disconnected from semiconductor production lines. Another major advance from the KAIST team is that the device can be fabricated using a CMOS-compatible process, meaning it can work well with traditional semiconductor manufacturing and could, in theory, be deployed directly in existing chip foundries.

What does that mean? It means this is not a lab concept that requires building everything from scratch, but an engineering solution that can be embedded in the industrial chain. If a cooling structure can be integrated into the existing manufacturing system at relatively low cost, the prospects for large-scale adoption rise sharply. For the semiconductor industry, this compatibility is often more important than pure peak performance, because the real test of value is whether a paper can become mass production.

From a broader perspective, the technology marks a shift in semiconductor thermal management thinking: cooling may no longer be just an “auxiliary system” for chips, but could become part of chip design itself. Compute, packaging, power delivery, and cooling will together form the four pillars of the next-generation chip architecture. Whoever breaks through in thermal management first will have a better chance of gaining an edge in the high-end chip race.

6. Application Outlook: Broad Expansion from AI Chips to Defense Electronics

The KAIST team expects the method to apply not only to large AI semiconductors and data-center cold plates, but also to high-performance computing (HPC), 3D-stacked semiconductors, power semiconductors, and defense electronics. This assessment is reasonable, because these scenarios share common traits: limited space, high thermal density, small cooling windows, and very high demands for efficiency and reliability.

In 3D-stacked chips, for example, multiple device layers are piled on top of each other, making heat more likely to accumulate inside. In power semiconductors, operating states change quickly and thermal shock is strong. In defense and avionics equipment, systems often need to be lightweight, compact, and highly reliable at the same time. If microchannel internal cooling can remain stable, it will create new design space for these fields.

Of course, the technology still faces challenges on the path from lab to industry. Long-term blockage risk, manufacturing consistency, chip reliability, compatibility with packaging materials, and coolant purity management all require further validation. But directionally, the technology clearly shows combined advantages of low cost, high efficiency, and manufacturability, making it strongly attractive from an engineering perspective.

Conclusion

KAIST’s ultra-efficient liquid-cooling technology marks a new stage for chip cooling, moving from “taking heat away from the outside” toward “precise internal temperature control.” By sending room-temperature water directly into a 3D manifold multi-channel microchannel structure inside the chip, the team not only lifted cooling performance to 10 times the previous record, but also achieved systematic optimization in pump power, temperature uniformity, manufacturing compatibility, and system cost.

For rapidly evolving AI hardware and high-performance electronic systems, the significance of this technology is far more than a single cooling innovation. It is more like a new infrastructure concept for the era of high-density compute. It proves that truly valuable breakthroughs do not necessarily rely on more complex materials or more expensive processes; they can also be achieved through smarter structure design and more efficient fluid organization.

As chip heat density continues to rise, cooling will no longer be a supporting role. It will be a core variable determining how much compute can actually be released. KAIST’s research shows that the next generation of semiconductor competition is not only about being faster, but also about being cooler.