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1.State Key Laboratory of Luminescence Science and Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
2.Key Laboratory of Advanced Structural Materials, Ministry of Education and School of Materials Science and Engineering and Advanced Institute of Materials Science, Changchun University of Technology, Changchun, China
3.Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, China
Wei Lü (lw771119@hotmail.com)
Xiaojuan Sun (sunxj@ciomp.ac.cn)
Dabing Li (lidb@ciomp.ac.cn)
Received:05 November 2025,
Revised:2026-04-19,
Accepted:20 April 2026,
Online First:02 June 2026,
Published:31 August 2026
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Zhang, Y. H. et al. Thermal Utilization on Chip. Light: Science & Applications, 15, 2871-2883 (2026).
Zhang, Y. H. et al. Thermal Utilization on Chip. Light: Science & Applications, 15, 2871-2883 (2026). DOI: 10.1038/s41377-026-02326-1.
The integration and miniaturization of chips lead to significant power consumption and heat accumulation. Typically
the energy consumption of cooling systems accounts for morn than 50% of the input energy. Current thermal management technologies do not offer solutions for on-chip thermal energy loss. Herein
we propose an on-chip integrated thermal recovery system
which can simultaneously achieve efficient heat dissipation. Present system on chips is based on hydrovoltaic generator technology
consisting of electrodes and gel. With the deep ultraviolet LED (236 nm) chip suffering from severe heat accumulation as a prototype
upon integration with the thermal recovery system
not only maintain the chip temperature below 40 ℃
but also converts waste heat into stored electrical energy
resulting in a 610.70% improvement in overall energy utilization efficiency. To demonstrate its general applicability in commercial CPU systems
we used the commercial Intel G3220 chip and as an example
by incorporating four HEG units
the temperature was reduced from 93 ℃ to below 60 ℃
effectively enhancing computational performance and extending the chip’s lifespan.
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