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A laser that can fire light pulses in one billionth of a second is set to produce structures 1000 times stronger, 1000 times faster — novel technique has applications for high-performance computing, quantum devices, and AI chip cooling

2026-01-17 21:30
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A laser that can fire light pulses in one billionth of a second is set to produce structures 1000 times stronger, 1000 times faster — novel technique has applications for high-performance computing, quantum devices, and AI chip cooling

Researchers demonstrate a laser-based method that alters heat flow in thin silicon films using scalable nanoscale surface patterning techniques.

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A laser that can fire light pulses in one billionth of a second is set to produce structures 1000 times stronger, 1000 times faster — novel technique has applications for high-performance computing, quantum devices, and AI chip cooling News By Efosa Udinmwen published 17 January 2026

Thermal conductivity drops due to controlled phonon scattering distances

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  • Heat flow is altered inside chip components instead of removed after buildup
  • Phonon motion is limited through nanoscale surface patterning
  • Ultrafast lasers enable nanoscale patterning at industrially relevant speeds

Today, most electronics rely on heat sinks, fans, or liquid cooling because the components inside chips conduct heat in fixed ways.

A new method designed by Japanese researchers lets engineers control how fast heat escapes from a material, rather than just trying to remove heat after it builds up.

The work describes a laser-based fabrication method that modifies how heat moves through thin silicon and silica films by directly shaping their surfaces at the nanoscale.

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Altering heat transport at the chip component level

The approach relies on ultrafast laser pulses, each lasting a femtosecond, to ablate material and create parallel grooves across the film surface.

These grooves form with carefully controlled spacing and depth that closely match the average distance phonons travel before scattering.

Because phonons are the primary carriers of heat in these components, restricting their movement predictably alters overall thermal conductivity.

The resulting features, known as femtosecond laser-induced periodic surface structures, show high uniformity over relatively large areas.

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When combined with conventional dry etching to adjust film thickness, the patterned surfaces exhibit a marked reduction in thermal conductivity.

Thermoreflectance measurements quantified this change, offering experimental confirmation rather than inferred behavior.

Numerical simulations also showed that the reduction arises mainly from limited phonon travel distances rather than changes in chemical composition or bulk material properties.

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A central claim of the study concerns fabrication speed. The fs-LIPSS process is reported to operate at a throughput more than 1000x faster than single-beam electron-beam lithography while still achieving nanoscale resolution.

This difference is substantial, especially for applications requiring large patterned areas, such as thermal layers integrated into data center-class processors.

The process is maskless and resist-free, which reduces procedural complexity and aligns with standard CMOS manufacturing constraints.

The technique has also been described as capable of wafer-scale implementation without introducing additional components or lithographic steps.

Because the method avoids resists and masks, it remains compatible with established semiconductor workflows.

The researchers describe the process as scalable, semiconductor-ready, and suitable for integration with existing fabrication lines.

The nanostructures are described as mechanically robust, with reports indicating strength levels up to 1000x higher than those produced using some conventional patterning approaches.

However, the available description provides limited detail on direct mechanical benchmarking or comparative testing methods.

The technique appears promising, and it is relevant for high-performance computing, quantum devices, and thermal management challenges associated with dense GPU clusters powering modern AI tools.

But wider adoption will depend on reproducibility, long-term stability, and cost under industrial conditions, especially at data center deployment scales.

Via Institute of Science Tokyo

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Efosa UdinmwenEfosa UdinmwenFreelance Journalist

Efosa has been writing about technology for over 7 years, initially driven by curiosity but now fueled by a strong passion for the field. He holds both a Master's and a PhD in sciences, which provided him with a solid foundation in analytical thinking.

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