UCLA Team Finds Metal With Record Heat Conductivity

University of California - Los Angeles

A UCLA-led, multi-institution research team has discovered a metallic material with the highest thermal conductivity measured among metals, challenging long-standing assumptions about the limits of heat transport in metallic materials.

Published in Science , the study is led by Yongjie Hu , a professor of mechanical and aerospace engineering at the UCLA Samueli School of Engineering. The team reported that metallic theta-phase tantalum nitride conducts heat nearly three times more efficiently than copper or silver, the best conventional heat-conducting metals.

Thermal conductivity describes how efficiently a material can carry heat. Materials with high thermal conductivity are essential for removing localized hotspots in electronic devices, where overheating limits performance, reliability and energy efficiency. Copper currently dominates the global heat-sink market, accounting for roughly 30% of commercial thermal-management materials, with a thermal conductivity of about 400 watts per meter-kelvin.

The UCLA-led team found that metallic theta-phase tantalum nitride, in contrast, has an ultrahigh thermal conductivity of approximately 1,100 W/mK, setting a new benchmark for metallic materials and redefining what is possible for heat transport in metals.

"As AI technologies advance rapidly, heat-dissipation demands are pushing conventional metals like copper to their performance limits, and the heavy global reliance on copper in chips and AI accelerators is becoming a critical concern," said Hu, who is also a member of the California NanoSystems Institute at UCLA. "Our research shows that theta-phase tantalum nitride could be a fundamentally new and superior alternative for achieving higher thermal conductivity and may help guide the design of next-generation thermal materials."

For more than a century, copper and silver have represented the upper bound of thermal conductivity among metals. In metallic materials, heat is carried by both free-moving electrons and atomic vibrations known as phonons. Strong interactions between electrons and phonons and phonon-phonon interactions have historically limited how efficiently heat can flow in metals. The UCLA discovery demonstrates that this long-standing benchmark can be surpassed.

Theoretical modeling suggested that theta-phase tantalum nitride could exhibit unusually efficient heat transport due to its unique atomic structure, in which tantalum atoms are interspersed with nitrogen atoms in a hexagonal pattern. The team confirmed the material's performance using multiple techniques, including synchrotron-based X-ray scattering and ultrafast optical spectroscopy. These measurements revealed extremely weak electron–phonon interactions, enabling heat to flow far more efficiently than in conventional metals.

Beyond microelectronics and AI hardware, the researchers say the discovery could impact a wide range of technologies increasingly limited by heat, including data centers, aerospace systems and emerging quantum platforms.

A leading researcher in electronics thermal management, Hu pioneered the experimental discovery of boron arsenide , another high-thermal-conductivity semiconductor material, in 2018. His group has since demonstrated high-performance thermal interfaces and gallium nitride devices integrating boron arsenide for cooling , highlighting the material's promise for next-generation semiconductor technologies.

The study's co-lead authors are Suixuan Li, Chuanjin Su and Zihao Qin — all graduate students of Hu's H-Lab at UCLA Samueli. Additional authors are from the U.S. Department of Energy's Argonne National Laboratory, Lawrence Berkeley National Laboratory, Tohoku University in Japan and the UC Irvine Materials Research Institute.

The research was funded in part by the U.S. Department of Energy and the National Science Foundation. Computational support was provided by the UCLA Institute for Digital Research and Education's Research Technology Group and Bridges-2 at the Pittsburgh Supercomputing Center.

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