High-performance plasmonic mid-infrared bandpass filters by inverse design.

Plasmonic spectral filters composed of periodic nanostructured metal films offer novel opportunities for the development of multispectral imaging technologies in the mid-infrared region. However, traditional plasmonic filters, which typically feature simplistic structures such as nanoholes or nanorings, are constrained by a narrow bandpass and significant crosstalk, leading to limited practical performance. Filters designed using inverse techniques allow a substantial degree of freedom in creating intricate structures that align with desired spectral characteristics, including a quasi-square spectral profile, high transmission, wide full width at half maximum, and reduced crosstalk. In this study, we have utilized an inverse design algorithm to engineer high-performance bandpass filters for the mid-infrared range, achieving an average transmittance exceeding 80% within the bandpass window and below 10% in the stop band, which is comparable to that of commercial multilayer Bragg filters. Nanofabrication processes were employed to transfer the designed pattern into the gold film on ZnS substrate that is transparent in the mid-infrared range. The resulting filters exhibit spectral performance analogous to that of the inversely designed models, making them suitable for direct integration with mid-infrared photodetector arrays in multispectral imaging systems.

High-Precision Multi-Object Tracking in Satellite Videos via Pixel-Wise Adaptive Feature Enhancement.

In this paper, we focus on the multi-target tracking (MOT) task in satellite videos. To achieve efficient and accurate tracking, we propose a transformer-distillation-based end-to-end joint detection and tracking (JDT) method. Specifically, (1) considering that targets in satellite videos usually have small scales and are shot from a bird's-eye view, we propose a pixel-wise transformer-based feature distillation module through which useful object representations are learned via pixel-wise distillation using a strong teacher detection network; (2) targets in satellite videos, such as airplanes, ships, and vehicles, usually have similar appearances, so we propose a temperature-controllable key feature learning objective function, and by highlighting the learning of similar features during distilling, the tracking accuracy for such objects can be further improved; (3) we propose a method that is based on an end-to-end network but simultaneously learns from a highly precise teacher network and tracking head during training so that the tracking accuracy of the end-to-end network can be improved via distillation without compromising efficiency. The experimental results on three recently released publicly available datasets demonstrated the superior performance of the proposed method for satellite videos. The proposed method achieved over 90% overall tracking performance on the AIR-MOT dataset.

Ultrasensitive Ebola Virus Antigen Sensing via 3D Nanoantenna Arrays.

Sensitive detection of pathogens is crucial for early disease diagnosis and quarantine, which is of tremendous need in controlling severe and fatal illness epidemics such as of Ebola virus (EBOV) disease. Serology assays can detect EBOV-specific antigens and antibodies cost-effectively without sophisticated equipment; however, they are less sensitive than reverse transcriptase polymerase chain reaction (RT-PCR) tests. Herein, a 3D plasmonic nanoantenna assay sensor is developed as an on-chip immunoassay platform for ultrasensitive detection of Ebola virus (EBOV) antigens. The EBOV sensor exhibits substantial fluorescence intensity enhancement in immunoassays compared to flat gold substrate. The nanoantenna-based biosensor successfully detects EBOV soluble glycoprotein (sGP) in human plasma down to 220 fg mL-1 , a significant 240 000-fold sensitivity improvement compared to the 53 ng mL-1 EBOV antigen detection limit of the existing rapid EBOV immunoassay. In a mock clinical trial, the sensor detects sGP-spiked human plasma samples at two times the limit of detection with 95.8% sensitivity. The results combined highlight the nanosensor's extraordinary capability of detecting EBOV antigen at ultralow concentration compared to existing immunoassay methods. It is a promising next-generation bioassay platform for early-stage disease diagnosis and pathogen detection for both public health and national security applications.

Nanoscale-driven crystal growth of hexaferrite heterostructures for magnetoelectric tuning of microwave semiconductor integrated devices.

A nanoscale-driven crystal growth of magnetic hexaferrites was successfully demonstrated at low growth temperatures (25-40% lower than the temperatures required often for crystal growth). This outcome exhibits thermodynamic processes of crystal growth, allowing ease in fabrication of advanced multifunctional materials. Most importantly, the crystal growth technique is considered theoretically and experimentally to be universal and suitable for the growth of a wide range of diverse crystals. In the present experiment, the conical spin structure of Co2Y ferrite crystals was found to give rise to an intrinsic magnetoelectric effect. Our experiment reveals a remarkable increase in the conical phase transition temperature by ∼150 K for Co2Y ferrite, compared to 5-10 K of Zn2Y ferrites recently reported. The high quality Co2Y ferrite crystals, having low microwave loss and magnetoelectricity, were successfully grown on a wide bandgap semiconductor GaN. The demonstration of the nanostructure materials-based "system on a wafer" architecture is a critical milestone to next generation microwave integrated systems. It is also practical that future microwave integrated systems and their magnetic performances could be tuned by an electric field because of the magnetoelectricity of hexaferrites.