Ferveret, an innovative developer of advanced liquid-cooling solutions for data centers inspired by nuclear reactor cooling systems, today announced that researchers at the Massachusetts Institute of Technology (MIT) are using its high-performance computing platform to accelerate AI-driven materials research for next-generation nuclear energy.

The collaboration with MIT researchers demonstrates how advanced thermal management can unlock up to 35% more usable compute from the same power envelope. By unlocking more power capacity, researchers can advance critical analysis and accelerate discoveries, putting compute to work for good.

“Ferveret’s philosophy for evaluating high-performance AI infrastructure is simple: rather than relying solely on synthetic benchmarks or artificial stress tests, the company believes real scientific workloads provide a more meaningful measure of system performance while creating tangible value for researchers and others who need the compute,” said Reza Azizian, Co-Founder and CEO of Ferveret.

MIT’s AI-driven materials research continuously pushes GPU infrastructure to its limits, providing an ideal environment to demonstrate how advanced cooling enables greater computational performance while accelerating scientific discovery.

“Access to Ferveret’s platform enables us to pursue research that simply would not be feasible with the computational resources typically available in academia. The ability to train larger models, iterate faster and run experiments continuously is accelerating our pace of discovery. Today, compute is becoming as fundamental to scientific discovery as the laboratory itself. Advances in AI will increasingly depend not only on better algorithms, but on access to the infrastructure that makes them possible,” said Ericmoore Jossou, Assistant Professor of Nuclear Science and Engineering and Electrical Engineering and Computer Science, and Head of the Materials in Extreme Environments Lab, MIT.

The computational demands of MIT’s research closely mirror those faced by organizations deploying large-scale AI infrastructure. By supporting one of the world’s leading research institutions, Ferveret is also demonstrating how advanced cooling can unlock greater performance for commercial AI deployments.

“Our AI workloads place sustained demands on GPU infrastructure that closely resemble the challenges found in production AI environments. That makes our research an ideal proving ground for Ferveret’s technology. At the same time, the additional compute available through Ferveret’s platform allows us to explore more ambitious models, complete research cycles faster and accelerate scientific discovery,” said DongHun Ryu, Graduate Researcher, Materials in Extreme Environments Lab, MIT.

AI-Driven Materials Discovery Accelerated

One project supported by Ferveret focuses on improving the analysis of coherent X-ray images collected from nuclear materials. Existing algorithms often struggle with the complexity of advanced reactor materials. Using Ferveret’s platform, researchers are developing AI-based approaches that improve the accuracy and reliability of X-ray image analysis.

“We are leveraging generative AI to solve long-standing challenges in understanding materials for next-generation nuclear energy. Our AI models are significantly more accurate than conventional approaches, but they also push the limits of today’s computing infrastructure,” added Jossou.

A second area of research involves developing machine learning interatomic potentials that predict material behavior at the atomic scale under extreme operating conditions. These models require substantial GPU resources during training while enabling simulations approaching the accuracy of density functional theory, one of the most computationally demanding methods in materials science.

Infrastructure Is Becoming the Next Frontier for AI

As AI models continue to grow, access to compute is increasingly constrained by power, cooling and infrastructure rather than silicon alone. By unlocking more compute from the same power envelope, Ferveret’s Adaptive Phase Cooling helps AI infrastructure operators scale more efficiently while reducing power consumption and water use.

This enables GPUs to sustain higher performance while reducing thermal overhead, unlocking up to 15% more server-level compute compared with today’s leading direct-to-chip cooling approaches. Combined with facility-level efficiency improvements, organizations can realize up to 35% more usable compute from the same power envelope.

Sustainability initiatives are central to Ferveret’s mission of making more computing power available for high-value applications by doing more with the same resources. This was made evident in the recent recognition on the Cleantech Group’s 2026 Cleantech 50 to Watch list.

“The next era of AI will be constrained less by chips than by infrastructure. Every watt we save becomes another watt available for AI. Seeing MIT researchers use that additional compute to accelerate discoveries in advanced nuclear materials demonstrates exactly why better cooling matters. The future of AI depends not only on more powerful processors, but on infrastructure that allows them to operate at their full potential,” said Azizian.

About the MIT Research

MIT’s Materials in Extreme Environments Lab develops advanced materials capable of operating under the demanding conditions found in next-generation energy systems. Led by Professor Ericmoore Jossou, the group combines materials science, advanced X-ray imaging, high-performance computing and artificial intelligence to accelerate the discovery and characterization of materials for nuclear energy and other extreme environments. Research publications resulting from work performed on Ferveret’s platform are expected to acknowledge the company’s contribution to the computing infrastructure supporting the research.

About Ferveret

Founded in 2021 by MIT alumni, Ferveret is an advanced cooling technology company building next-generation thermal solutions for AI data centers. Ferveret’s Adaptive Phase Cooling is inspired by a technique used in nuclear reactor systems known as subcooled boiling, which dramatically increases heat transfer efficiency while operating near ambient pressure. The technology enables higher rack densities, improved energy efficiency, and reduced infrastructure complexity compared to conventional liquid cooling approaches. Its mission is to eliminate power waste and reduce the use of natural resources for the world’s digital infrastructure. Ferveret is headquartered in San Jose, California. For more information, visit https://www.ferveret.com/.

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