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Dual-Zero-Scattering in Diffusive Transport.

Yiyang Zhang1, Jinrong Liu2, Liujun Xu3

  • 1Fudan University, Department of Physics, State Key Laboratory of Surface Physics, and Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Shanghai 200438, China.

Physical Review Letters
|May 29, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Researchers developed a dual-zero-scattering metamaterial regime to achieve true transparency in diffusive fields. This breakthrough overcomes the trade-off hindering invisibility cloaks and enables noninvasive devices for thermal and wave systems.

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Area of Science:

  • Metamaterials
  • Diffusive physics
  • Wave phenomena

Background:

  • Metamaterial cloaking in diffusive fields is limited by a trade-off between external scattering suppression and internal field distortion.
  • Existing metamaterial shells cannot achieve perfect transparency due to inevitable internal field manipulation.

Purpose of the Study:

  • To overcome the fundamental trade-off in metamaterial cloaking.
  • To achieve true transparency in diffusive fields by eliminating scattering both externally and internally.
  • To establish a general paradigm for noninvasive devices in diffusion-based systems.

Main Methods:

  • Developed a dual-zero-scattering regime integrating coordinate transformation and scattering cancellation.
  • Utilized deep-learning-optimized microstructures to realize anisotropic thermal conductivity.
  • Performed numerical simulations and experimental validations.
  • Main Results:

    • Demonstrated simultaneous elimination of scattering in the background medium and metamaterial shell.
    • Achieved perfect transparency, overcoming the conventional trade-off.
    • Successfully applied the concept to thermal sensors, cloaks, and concentrators.

    Conclusions:

    • The dual-zero-scattering regime provides a general paradigm for designing truly noninvasive devices.
    • This approach has promising extensions to acoustics and electromagnetics.
    • Deep-learning-optimized microstructures are key to realizing the required material properties.