Abstract:An enhancement of mid-wavelength infrared absorbance is achieved via a cost-effectively chemical method to bend the flakes by grafting two types of alkane octane （C₈H₁₈） and dodecane （C₁₂H₂₆） onto the surface terminals respectively. The chain-length of alkane exceeds the bond-length of surface functionalities Tx （=O，-OH，-F） so as to introduce intra-flake and inter-flake strains into Ti₃C₂T_x MXene. The electronic microscopy （TEM/AFM） shows obvious edge-fold and tensile/compressive deformation of flake. The alkane termination increases the intrinsic absorbance of Ti₃C₂T_x MXene from no more than 50% down to more than 99% in the mid-wavelength infrared region from 2.5 μm to 4.5 μm. Such an absorption enhancement attribute to the reduce of infrared reflectance of Ti₃C₂T_x MXene. The C-H bond skeleton vibration covers the aforementioned region and partially reduce the surface reflectance. Meanwhile， the flake deformation owing to edge-fold and tensile/compression increase the specific surface area so as to increase the absorption as well. These results have applicable value in the area of mid-infrared camouflage.

Abstract:In this paper， the research results of 12.5 μm long-wavelength infrared InAs/GaSb superlattice focal plane arrays were reported. The superlattice structure was grown on GaSb substrate using molecular beam epitaxy （MBE） technology. The respective structure of absorption region is 15ML （ InAs） /7ML （ GaSb）. The detector adopts PBπBN double barrier structure to suppress the dark current. A long-wave focal plane detector with the size of 1 024×1 024 and the pixel center-to-center distance of 18 μm was developed. The detector is packaged by a metal dewar， and a superlattice long-wavelength detector cryocooler assembly is formed by coupling with a refrigerator. At 60 K measurement， the detector has 50% cut-off wavelength of 12.5 μm. The detector has a peak detectivity of 6.6×10¹⁰ cm?Hz^1/2/W ， dead pixels rate of 1.05% and a noise equivalent temperature difference （NETD） is 21.2 mK. The Infrared images of the test have been taken clearly using the infrared imaging detector.

Abstract:Hexagonal boron nitride （h-BN） is found to have widespread application， owing to its outstanding properties， including gate dielectrics， passivation layers， and tunneling layers. The current studies on the fundamental physical properties of these ultrathin h-BN films and the electron tunneling effect among them are inadequate. In this work， the effective mass in h-BN was successfully determined through a combined approach of experimental and theoretical research methods by fitting the current-voltage curves of metal/insulator/metal structures. It was observed that within a range of 4~22 layers， the effective mass of h-BN exhibits a monotonic decrease with an increase in the number of layers. Precisely ascertain the physical parameters of the Fowler-Nordheim tunneling model in the context of electron tunneling in h-BN by utilizing the extracted effective mass. Additionally， the impact of fixed charges at the metal/h-BN interface and various metal electrode types on Fowler-Nordheim tunneling within this structure was investigated utilizing this physical parameter in Sentaurus TCAD software. This work is informative and instructive in promoting applications in the fields of h-BN related infrared physics and technology.

Abstract:The response wavelength of the blocked-impurity-band （BIB） structured infrared detector can reach 200 μm， which is the most important very long wavelength infrared astronomical detector. The ion implantation method greatly simplifies the fabrication process of the device， but it is easy to cause lattice damage， introduce crystalline defects， and lead to the increase of the dark current of detectors. Herein， the boron-doped germanium ion implantation process was studied， and the involved lattice damage mechanism was discussed. Experimental conditions involved using 80 keV energy for boron ion implantation， with doses ranging from 110¹³ to 310¹⁵ cm^-2. After implantation， thermal annealing at 450 °C was implemented to optimize dopant activation and mitigate the effects of ion implantation. Various sophisticated characterization techniques， including X-ray diffraction （XRD）， Raman spectroscopy， X-ray photoelectron spectroscopy （XPS）， and secondary ion mass spectrometry （SIMS） were used to clarify lattice damage. At lower doses， no notable structural alterations were observed. However， as the dosage increased， specific micro distortions became apparent， which could be attributed to point defects and residual strain. The created lattice damage was recovered by thermal treatment， however， an irreversible strain induced by implantation still existed at the high doses.

Abstract:The pursuit of ultra-small pixel pitch InGaAs detectors necessitates a meticulous approach to addressing challenges associated with crosstalk reduction and dark current minimization. By developing the fabrication process technology of micro-mesa InGaAs detector， a test structure featuring a micro-mesa InGaAs photosensitive chip with 10 μm and 5 μm pixel pitch was successfully prepared. Subsequently， a comprehensive investigation was conducted to analyze the impact of the micro-mesa structure on crosstalk and dark current characteristics of the InGaAs detector. The obtained results revealed the efficacy of the micro-mesa structure in effectively suppressing crosstalk between adjacent pixels when the isolation trench etches into the absorption layer. However， a noteworthy challenge emerged as the fabrication processes induced material damage， leading to a considerable increase in recombination current and Ohmic leakage current. This adverse effect， in turn， manifested as a dark current escalation by more than one order of magnitude. The significance of these findings offers a novel perspective for the manufacturing of ultra-small pixel pitch InGaAs focal plane detectors.

Abstract:The master oscillator power amplifier （MOPA） laser is receiving increasing attention due to its ability to achieve high power and beam quality output. In order to improve the polarization degree of MOPA laser and reduce the efficiency loss during polarization combining， InGaAs/AlGaAs compressive single quantum well was used in the active region. The optical confinement factor of TE-mode in ridge waveguide was improved by 1.35 μm deep etching， whereas the TE optical gain in tapered amplifier was increased through on-chip metal stress regulation. Combining the two schemes not only improves the degrees of polarization （DOP） of two sections， but also reduces the polarization angle difference. Finally， 11W@15A continuous output and over 90% DOP of the MOPA have been achieved by standard process fabrication.

Abstract:Based on the GaAs planar Schottky diode process， a W band wideband frequency tripler MMIC is designed with a reverse parallel diode pair. By combining the finite element method and equivalent circuit method， an accurate equivalent circuit model of the planar Schottky diode is built in the frequency range of 10~280 GHz. The nonlinear harmonic balance tool is utilized to achieve the optimal frequency tripler design in the W band. The measurement results show that the frequency multiplication loss is less than 15 dB under 17 dBm driving power， and efficiency up to 6.7%. The chip size is 0.80 mm×0.65 mm×0.05 mm．

Abstract:Synthetic aperture radar （SAR） is a high-resolution two-dimensional imaging radar. However， during the imaging process， SAR is susceptible to intentional and unintentional interference， with radio frequency interference （RFI） being the most common type， leading to a severe degradation in image quality. To address the above problem， numerous algorithms have been proposed. Although inpainting networks have achieved excellent results， their generalization is unclear. Whether they still work effectively in cross-sensor experiments needs further verification. Through time-frequency analysis to interference signals， this work finds that interference holds domain invariant features between different sensors. Therefore， this work reconstructs the loss function and extracts the domain invariant features to improve its generalization. Ultimately， this work proposes a SAR RFI suppression method based on domain invariant features， and embeds the RFI suppression into SAR imaging process. Compared to traditional notch filtering methods， the proposed approach not only removes interference but also effectively preserves strong scattering targets. Compared to PISNet， our method can extract domain invariant features and holds better generalization ability， and even in the cross-sensor experiments， our method can still achieve excellent results. In cross-sensor experiments， training data and testing data come from different radar platforms with different parameters， so cross-sensor experiments can provide evidence for the generalization.

Abstract:Aiming to address the issue of high complexity in estimating the parameters of the attributed scattering center model （ASCM） in synthetic aperture radar （SAR） images， a sparse representation parameter estimation method that integrates information from the image domain is proposed. Firstly， the improved watershed algorithm is used to segment the scattering centers of different regions. Subsequently， based on the segmentation results， the frequency domain sparse representation dictionary is decoupled and applied in a serialized manner for scattering center parameter estimation using orthogonal matching pursuit to reduce algorithm complexity. Based on simulated data and measured MSTAR data， the effectiveness and efficiency of the proposed parameter extraction method were validated， and the optimization of theoretical complexity was analyzed. The results indicate that this method can significantly reduce the time and space complexity of the algorithm while achieving results close to those of the conventional orthogonal matching pursuit algorithm. The proposed method can be used for the efficient extraction of scattering center parameters in SAR images.

Abstract:As a key parameter for characterizing the radiation characteristics of objects， emissivity has significant value in accurate measurement for high-temperature target identification， material modification， and regulation of metal smelting process. The multispectral radiation method for measuring emissivity has become a research hotspot due to its non-contact and fast measurement speed advantages， and its measurement accuracy is determined by the solution accuracy of the underdetermined equation system. At present， the research on the solution accuracy of the underdetermined system of equations mainly focuses on the error of the equation solving algorithm， ignoring the measurement error of the spectrometer itself， which leads to the failure of controlling the system error in a reasonable way. In this paper， based on the assumption of retardation with wide application range and high measurement accuracy， the influence of the number of spectral channels and signal-to-noise ratio on the emissivity measurement error under different conditions is simulated. The parameter configurations of the spectrometer under the corresponding conditions are determined and the effect of emissivity measurement is experimentally verified. The experimental results show that， using the multispectral radiation method based on the slow-change assumption， the number of spectral channels of the spectrometer should be not less than 400 and the signal-to-noise ratio should not be less than 1000 in order to make the blackbody emissivity measurement error less than 1%. For the targets with complex emissivity changes， the spectrometer should have at least 1 000 spectral channels and signal-to-noise ratios of more than 1 200 in order to make the measurement error less than 1%. Taking into account the matching relationship between algorithm errors and spectrometer parameters is the key to effectively controlling system errors and obtaining more accurate emissivity measurement results. This provides a new basis and solution for the precise measurement of emissivity using multispectral radiation methods， which is of great significance for the accurate identification of high-temperature targets and related applications.

Abstract:Metasurfaces provide a potent platform for the dynamic manipulation of electromagnetic waves. Coupled with phase-change materials， they facilitate the creation of versatile metadevices， showcasing various tunable functions based on the transition between amorphous and crystalline states. However， the inherent limitation in tunable states imposes constraints on the multiplexing channels of metadevices. Here， this paper introduces a novel approach - a multi-functional metadevice achieved through the two-level control of the encoding phase-change metaatoms. Utilizing the phase-change material Ge₂Sb₂Se₄Te₁ （GSST） and high refractive-index liquid diiodomethane （CH₂I₂）， this paper showcases precise control over electromagnetic wave manipulation. The GSST state governs the tunable function， switching it ON and OFF， while the presence of liquid in the hole dictates the deflection angle when the tunable function is active. Importantly， our tunable coding metasurface exhibits robust performance across a broad wavelength spectrum. The incorporation of high refractive-index liquid extends the regulatory dimension of the metadevice， enabling dynamic switching of encoding bit levels. This two-level tunable metadevice， rooted in phase-change materials， presents a promising avenue for the dynamic control of functions.

Abstract:This work introduces a novel method for measuring thin film thickness， employing a multi-wavelength method that significantly reduces the need for broad-spectrum data. Unlike traditional techniques that require several hundred spectral data points， the multi-wavelength method achieves precise thickness measurements with data from only 10 wavelengths. This innovation not only simplifies the process of spectral measurement analysis but also enables accurate real-time thickness measurement on industrial coating production lines. The method effectively reconstructs and fits the visible spectrum （400~800 nm） using a minimal amount of data， while maintaining measurement error within 7.1%. This advancement lays the foundation for more practical and efficient thin film thickness determination techniques in various industrial applications.

Abstract:An LD directly-pumped solid-state laser is considered to be one of the most promising mid-infrared light sources because of its simple principle， small size， and compact structure for the generation of mid-infrared （MIR） lasers in the 3~5 μm band. However， the quantum defect of LD directly-pumped MIR solid-state lasers will be much larger than that of ordinary near-infrared LD pumped solid-state lasers， which may lead to thermal damage and limit their development. In order to solve this problem， the methods of reducing the specific surface area of the crystal and improving the thermal energy released by the crystal structure are discussed， and the optimal length of the laser crystal is determined. The cooling structures of barium yttrium fluoride laser crystals （Ho³⁺：BY₂F₈） of different lengths were studied by thermal simulation using COMSOL software. The experimental results show that the output power can be increased and the thermal stress in the laser crystal can be alleviated by using the laser crystal whose length is slightly shorter than that of the cooler. The final experiment shows that when the pump repetition rate is 15 Hz and the pulse width is 90 μs， the single pulse energy is 7.28 mJ at the output wavelength of 3.9 μm， which is about 3 times as large as that of the crystal with the length of 10 mm （2.81 mJ）. Such results should be another breakthrough of our team since the first directly-pumped solid-state MIR laser was realized more than a year ago. It might pave the way for the construction of a feasible MIR laser in the near future.

Abstract:This article introduces a method of achieving high polarization extinction ratio using a subwavelength grating structure on a lithium niobate thin film platform， and the chip is formed on the surface of the lithium niobate thin film. The chip， with a length of just 20 μm， achieved a measured polarization extinction ratio of 29 dB at 1 550 nm wavelength. This progress not only proves the possibility of achieving a high extinction ratio on a lithium niobate thin film platform， but also offers important technical references for future work on polarization beam splitters， integrated fiber optic gyroscopes， and so on.

Abstract:With a single-photon detector， photon-counting LiDAR （PCL） captures a large amount of background noise along with the target scattered/reflected echo signals， because of the influence of factors such as the background environment， target characteristics， and instrument performance. To accurately extract the signal photons on the ground surface from a noisy photon point cloud （PPC）， this paper presents an adaptive denoising approach for PPC using two levels of voxels. First， coarse denoising is performed utilizing large-scale voxels， which are built based on the spatial distribution features of the PPC. The density of the voxel is then used to select the voxels that contained dense signal photons. Second， fine denoising with small-scale voxels is conducted. These voxels are built using the nearest neighbor distance， and a topologicalrelationship between voxels is used to further extract voxels containing signal photons aggregated on the ground surface. Finally， this method is performed on the PPC from ATL03 datasets collected by the Ice， Cloud， and Land Elevation Satellite-2 both during daytime and at night and compared with the improved Density-Based Spatial Clustering of Applications with Noise （DBSCAN）， improved Ordering Points to Identify the Clustering Structure （OPTICS）， and the method used in the ATL08 datasets. The results show that the proposed method has the best performance， with precision， recall， and F1 score of 0.98， 0.97， and 0.98， respectively.

Abstract:The encoding aperture snapshot spectral imaging system， based on compressive sensing theory， can be regarded as an encoder， which can efficiently obtain compressed two-dimensional spectral data and then decode it into three-dimensional spectral data through deep neural networks. However， training the deep neural networks requires a large amount of clean data that is difficult to obtain. To address the problem of insufficient training data for deep neural networks， a self-supervised hyperspectral denoising neural network based on neighborhood sampling is proposed. This network is integrated into a deep plug-and-play framework to achieve self -supervised spectral reconstruction. The study also examines the impact of different noise degradation models on the final reconstruction quality. Experimental results demonstrate that self-supervised learning method enhances the average peak signal-to-noise ratio by 1.18 dB and improves the structural similarity by 0.009 compared with the supervised learning method. Additionally， it achieves better visual reconstruction results.

Abstract:To avoid the accumulation of estimation errors from explicitly aligning multi-frame features in current infrared small-dim target detection algorithms， and to alleviate the loss of target features due to network downsampling， a progressive spatio-temporal feature fusion network is proposed. The network utilizes a progressive temporal feature accumulation module to implicitly aggregate multi-frame information and utilizes a multi-scale spatial feature fusion module to enhance the interaction between shallow detail features and deep semantic features. Due to the scarcity of multi-frame infrared dim target datasets， a highly realistic semi-synthetic dataset is constructed. Compared to the mainstream algorithms， the proposed algorithm improves the probability of detection by 4.69% and 4.22% on the proposed dataset and the public dataset， respectively.

Abstract:Person re-identification is the task of retrieving a specified target from multiple data sources. The difference between infrared （IR） and visible light （VIS） images is large， and cross-modal retrieval of visible light and infrared images is one of the main challenges. In order to have the same retrieval ability even in low light or at night， the judgment needs to be achieved by combining cross-modal modeling of infrared images. In this paper， we propose a new method of guiding attention through human keypoints， where global features are split into local features by keypoint guidance， and then the original model is retrained with the generated local masks to strengthen the attention to different local information. Using this method， the model can better understand and utilize the key regions in the image， thus improving the accuracy of the person re-identification task.