Fengyu Liu

Magnetoelectric heterostructures integrating piezoelectric and magnetostrictive phases have emerged as a compelling material platform for investigating high-frequency magnetization dynamics and magnetoelastic coupling via acoustic wave excitation. This work presents magnetically tunable 1.015 GHz acoustic delay lines (ADLs) based on AlN/FeGaB heterostructure films, demonstrating both in-band phase and amplitude modulation capabilities. By investigating three characteristic frequency peaks (997.2 MHz, 1015.7 MHz, and 1027.5 MHz) within the device passband, it is observed that tunability tends to be enhanced near the modal peak frequencies where insertion loss is low. Under a magnetic field of 160 Oe with the acoustic wave direction perpendicular to the magnetic field (θ = 90°), the device achieves a maximum differential phase shift of 4.07° and an amplitude modulation of approximately 0.25 dB at 1015.7 MHz. Furthermore, linear phase and amplitude modulations of 3.23°/120 Oe and 0.19 dB/170 Oe are obtained at θ = 90°. These results experimentally demonstrate the feasibility of magnetic-field-engineered control in Lamb-wave acoustic delay lines, highlighting their strong potential for reconfigurable RF front-end applications.

Photoacoustic (PA) imaging technology integrates the deep penetration depth of ultrasound imaging with the high resolution of optical imaging, demonstrating significant potential in biomedical applications. Many preclinical studies and clinical applications urgently require a portable, high-quality, low-cost, and fast imaging system. Thus, translating advanced image reconstruction algorithms into hardware implementations is highly desired. However, existing iterative PA image reconstructions, although exhibit higher accuracy than the delay-and-sum algorithm, suffer from high computational cost. In this paper, we introduce a novel model-based hardware architecture for palm-size PA tomography (palm-PAT), aiming at enhancing both the speed and performance of image reconstruction at a much lower system cost. To achieve this, we propose an innovative data reuse method that significantly reduces the consumption of hardware storage resources, achieving a reduction of approximately 75% in hardware storage requirements. We conducted experiments utilizing the FPGA implementation of the algorithm, using phantom, human finger data in vivo and ex vivo breast tumor data to verify the feasibility of the proposed method. The results demonstrate that our proposed architecture can substantially reduce system cost while maintaining high imaging performance. The novel hardware architecture design of the model-based algorithm achieves a speedup of up to approximately 270 times compared to the CPU, while the corresponding energy efficiency ratio is improved by more than 2700 times.

Photoacoustic (PA) imaging technology combines the advantages of optical imaging and ultrasound imaging, showing great potential in biomedical applications. Many preclinical studies and clinical applications urgently require fast, high-quality, low-cost and portable imaging system. Translating advanced image reconstruction algorithms into hardware implementations is highly desired. However, existing iterative PA image reconstructions, although exhibit higher accuracy than delay-and-sum algorithm, suffer from high computational cost. In this paper, we introduce a model-based hardware acceleration architecture based on superposed Wave (s-Wave) for palm-size PA tomography (palm-PAT), aiming at enhancing both the speed and performance of image reconstruction at a much lower system cost. To achieve this, we propose an innovative data reuse method that significantly reduces hardware storage resource consumption. We conducted experiments by FPGA implementation of the algorithm, using both phantoms and in vivo human finger data to verify the feasibility of the proposed method. The results demonstrate that our proposed architecture can substantially reduce system cost while maintaining high imaging performance. The hardware-accelerated implementation of the model-based algorithm achieves a speedup of up to approximately 270 times compared to the CPU, while the corresponding energy efficiency ratio is improved by more than 2700 times.

Recently, there has been a growing demand for high-speed mid-wave infrared (MWIR) photodetectors (PDs) driven by the emergence of new fields, such as free-space communication and frequency comb spectroscopy. In this study, we investigated a high-speed InAs/GaSb type-II superlattice (T2SL) MWIR uni-traveling carrier (UTC) PD with relatively low dark current and high responsivity. We also perform an inductive peaked dewar packaging on the PD to be user-friendly and allow cryogenic operation. The original on-wafer PD shows a dark current density of 54.05 A/cm ² at 300 K, along with a responsivity exceeding 0.36 A/W at 4.5 μm and a 3-dB bandwidth of 3.83 GHz at −5 V bias. The inductive-peaked device in dewar packaging demonstrates a dark current density of 1.65×10 ⁻⁵ A/cm ² at 77 K, and a responsivity of 0.39 A/W at 4 μm, and a 3-dB bandwidth of 5.29 GHz.

When AlN thin films are deposited directly on the high-resistance silicon (HR-Si) substrate, a conductive layer will be formed on the HR-Si surface. This phenomenon is called the parasitic surface conduction (PSC) effect. The presence of the PSC effect will increase the power consumption of electronic components. Therefore, it is necessary to reduce the PSC effect. In prior technology, the polysilicon layer is usually used as the trap-rich layer to reduce the PSC effect. Experiments show that compared to AlN films deposited directly on HR-Si, the AlN substrates with polysilicon introduced on HR-Si have less radio frequency (RF) loss. To verify the effect of polysilicon on RF loss, polysilicon films of three different thicknesses and several different roughnesses were introduced. The results show that the thickness of the polysilicon will affect the RF loss, while the roughness has almost no effect on it. The polysilicon trap-rich layer can reduce the RF loss, which gradually becomes smaller as the polysilicon thickness increases.