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Xiaofan Ji

Publications and source records attributed to Xiaofan Ji.

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Breaking the trade-off between invisibility and sensitivity in electromagnetic sensing

Weak electromagnetic signals demand highly sensitive sensors, yet increasing a sensor's sensitivity inevitably strengthens its interaction with the surrounding field, producing scattering that perturbs the very signals being measured. Conversely, existing cloaking strategies suppress scattering only by isolating the sensor from incident waves, thereby compromising signal reception. Resolving this long-standing trade-off between invisibility and sensitivity has remained an outstanding challenge. Here we overcome this dilemma through an integrated transformation-optical architecture that co-designs the entire sensing system, including the electrically large sensor body, the subwavelength sensing probe, and their electrical interconnection. The proposed multifunctional core-shell structure guides incident waves around the sensor body while simultaneously concentrating them into the sensing region without disturbing the external electromagnetic field. A deep-subwavelength aperture preserves electrical connectivity without degrading either cloaking or field concentration, enabling invisible sensing within a single platform. A microwave prototype based on practical optic-null-medium metamaterials experimentally demonstrates broadband scattering suppression exceeding 3 dB together with an average sixfold enhancement of the detected signal over 4.9-5.1 GHz. By simultaneously eliminating measurement-induced field perturbation and amplifying the local sensing field, our approach establishes a general framework for invisible yet highly responsive electromagnetic sensors, opening new opportunities for weak-signal detection in biomedical diagnostics, secure communications, quantum technologies, and deep-space exploration.

physics.optics

Deep Learning-Enabled Invisible Electromagnetic Scattering Amplifier

With the rapid development of micro-electro-mechanical systems, electrically small micro-targets, such as subwavelength micro unmanned aerial vehicles and bionic mosquito robots, exhibit ultra-low scattering cross section, which brings severe challenges to their effective detection. To address this problem, an Invisible Electromagnetic Scattering Amplifier (IESA) is designed by combining finite-element electromagnetic simulation with a forward lossless tandem neural network. The IESA realizes the dual-functional integration of intrinsic electromagnetic invisibility (near-zero scattering) for itself and significant scattering amplification for subwavelength targets entering its air sensing region. Electromagnetic simulations verify that the designed IESA can achieve a stable scattering amplification effect on subwavelength targets with a characteristic size of approximately 0.1λ0, regardless of their spatial positions or geometric shapes, with a maximum scattering cross section amplification factor of 8.58. The IESA breaks the technical bottleneck of the separate design of electromagnetic invisibility and scattering amplification functions. It shows potential for applications in the fields of radar detection, anti-terrorism security, micro-target monitoring, and adaptive electromagnetic sensing.

physics.optics