In view of the limitations associated with traditional single-spot laser solid-state phase transformation temperature control methods in complex curved workpieces, this paper proposes a multi-input multi-output (MIMO) temperature decoupling control strategy based on active disturbance rejection control (ADRC). first, a finite element model of multi-spot laser-induced solid-state phase transformation was developed, and a model-order reduction method was applied to extract the key dynamic characteristics of the system, significantly reducing computational complexity and laying a foundation for effective control. Subsequently, to address the high-frequency jitter problem encountered by the conventional fal function within small-error regions, an improved bfal function based on Bernstein polynomials was proposed, thereby enhancing system observation accuracy and disturbance rejection capability. Moreover, an improved particle swarm optimization (PSO) algorithm was used to tune the parameter of ADRC controllers, effectively accelerating the optimization process. Finally, co-simulations conducted on the MATLAB/Simulink and COMSOL platforms demonstrated that the proposed PSO-ADRC controller achieves superior performance in terms of response speed, overshoot reduction, and steady-state accuracy compared to the conventional PID and standard ADRC methods. The method thus provides an efficient and precise solution for multi-spot laser solid-state phase transformation temperature control in complex curved workpieces.

With the rapid development of science and technology, high-speed optical imaging and ultrafast diagnostic techniques have become increasingly important in various fields such as science, industry, defense, and medicine. As an ultrafast optical phenomenon detection instrument, the synchroscan streak camera, when used in conjunction with high-repetition-rate lasers, can achieve high-precision time-synchronized pump-probe experiments. By accumulating and amplifying weak optical signals, it enables high signal-to-noise ratio detection. However, existing synchronous scanning circuits, when operating in long-term mode, accumulate high-frequency noise from signal source devices, and there is a lack of specific impedance matching design methods, which affects the improvement of the time resolution performance of streak camera. This paper comprehensively considers various transformer structures and design schemes, and conducts resonant matching design based on spiral resonators. Through finite element simulation, relevant simulation studies are carried out. By adjusting the parameters of the primary coil of the resonator, the output impedance of the RF power amplifier and the capacitive load are matched. The resonant coupling boost study of the design model shows that a high peak voltage can be output under a certain power input, verifying the effectiveness of the spiral resonant method. The comparative analysis of noise response and time jitter indicates that the design method can further enhance the time resolution performance of synchronous scanning. resolution performance of synchronous scanning.

Facing the urgent demand for high-performance, customized electromagnetic protection materials driven by increasingly intelligent electronic information systems, traditional research and development (R&D) models face severe limitations due to complex multi-parameter coupling, high trial-and-error costs, and difficulties in cross-scale design, hindering their ability to meet the need for efficient R&D. Artificial intelligence (AI), leveraging data-driven approaches and algorithmic optimization, offers a transformative paradigm to overcome these limitations. This paper systematically reviews AI-empowered research in electromagnetic protection materials. It begins by analyzing the key characteristics and core challenges in the R&D of these materials, highlighting the high suitability of AI for this domain. Subsequently, it illustrates representative research cases from both forward prediction and inverse design perspectives within the field. Finally, the paper identifies existing challenges concerning data availability, physical interpretability of AI models, and practical application deployment barriers. Specific considerations are proposed in three aspects: constructing specialized electromagnetic material gene databases, developing physics-informed neural networks that integrate data with physical principles, and emphasizing the need to promote domain-specific data sharing and establish standardized protocols, so as to pave the way for the intelligent development of next-generation electromagnetic protection materials.

This paper introduces the working principle, composition and configuration of a miniaturized high-throughput neutron source system. It systematically introduces the piezoelectric pulse power source technology, nuclear reaction design technology, spherical electromagnetic field generation technology, particle proximity acceleration technology, particle polarization and resonance collision technology required for the development of this neutron source system. A complete neutron source physical system was developed and tested for energy spectrum and flux. The expected physical phenomena were observed in the experiments, and the occurrence of nuclear reactions was proved by online and offline neutron measurement methods, and the test results showed that the neutron radiation flux of the new miniature neutron source with a diameter of 2 cm and a length of 4 cm reached the level of 1010 n/(cm2·s), which belongs to strong neutron radiation source.

To effectively solve the problem of strong electromagnetic pulse power required to drive particle reactions, a new pulse power synchronous amplification technology based on hydrogen plasma loading and wave-particle resonance mechanism is studied on the basis of piezoelectric ceramic stack pulse source. The amplification mechanism is as follows: first, the energy of hydrogen molecule bonding orbitals is lower than that of antibonding orbitals, and internal energy will be released during the ionization process to promote the efficient occurrence of the ionization process driven by pulse power; Second, after the ionization of hydrogen atoms, the electromagnetic field and electrons undergo wave-particle resonance, and the electron energy is synchronously converted into electromagnetic field energy. After the amplification of wave-particle resonance, a stronger electromagnetic pulse is obtained, which can form a spherical electromagnetic field when applied to the spiral electrode, and has an extremely high acceleration gradient, which can accelerate a large number of protons produced after efficient ionization of hydrogen atoms. The above theory is effectively proved through experimental tests and simulation analysis, and this research is expected to lay a foundation for a miniaturized and low-cost proton generator driven by strong electromagnetic pulses.

The quantitative study of combat effectiveness index is crucial for the informatization construction of the armed forces. To solve the problems of limits of quantitative research, low method accuracy, and weak robustness in the study of combat effectiveness index, and to break through the limitations of dominating complex rules, multivariate mathematical models, and strong coupling of influencing factors in the combat effectiveness index function, inspired by the mathematical analysis methods of rules in fuzzy logic theory, we proposed a local approximation based method for fitting combat effectiveness index function. Combining the powerful self-learning and self-deduction capabilities of neural networks, we constructed a corresponding quantitative calculation model based on radial basis function (RBF). Simulation comparative experiments show that the proposed method has an error rate of about 2% and 6% lower than the current best performing method using global approximation, and exhibits stronger robustness. Our method has strong practicality, can be migrated to other military fields, and has good engineering application prospects.

To optimize the performance of the pulsed xenon lamp sterilization device, the influence of spectral range and specifications of lamps on the sterilization effect is studied based on a self-developed high-energy microsecond pulse power supply and xenon lamps with different specifications. The results show that in the UV-visible spectrum of a xenon lamp with an arc length of 50 mm and a pressure of 50 kPa, the UV accounts for 38.5% and the UVC accounts for 17.6%. Increasing the arc length and decreasing the pressure can both increase the spectral intensity, and the latter can also increase the ratio of UV. The xenon lamp with an arc length of 100 mm and a pressure of 50 kPa can basically inactivate all Escherichia coli in 3 s with a discharge energy of 20 J. The sterilization rate is positively correlated with arc length and discharge energy of the lamp, negatively correlated with pressure. All bands of xenon lamp radiation have sterilization effects, with UV accounting for 87.7% in log value and the wavelength band less than 280 nm accounting for 64.6%. The AFM images show that pulsed xenon lamp changed the morphology and mechanical properties of Escherichia coli, hence the bacteria shrank, their surface roughness, elasticity, and adhesion increased.

A simple and effective improved A* algorithm is proposed to solve the problem of robot path planning in the integrated installation of large-scale laser devices. Compared with the traditional A* algorithm, the algorithm has been improved in three steps. Firstly, the walking direction is limited, which avoids the phenomenon of crossing obstacles occurred in the traditional A* algorithm; Secondly, the heuristic function is optimized as a weighted Manhattan distance function, which accelerates the expansion of nodes in the x direction or y direction, and reduces the surge of traversal nodes caused by limiting the walking direction. Thirdly, the turning penalty term is introduced to reduce the number of turns in the path planning process, and improve the search efficiency and quality. The performance of the three-step improved A* algorithm is verified in different size raster maps, and compared with the traditional A* algorithm. Experimental results show that in simple maps, the number of nodes traversed by the three-step improved A* algorithm is slightly higher than that of the traditional A* algorithm, and the number of turns is equivalent to that of the traditional A* algorithm, but the obstacle avoidance performance is obviously better than that of the traditional A* algorithm, which is more conducive to the safe walking of robots. In complex maps, considering the priority relationship of traversal nodes, turn times and path length, the parameters of the three-step improved A* algorithm can be adjusted to obtain the optimal path planning result.

Terahertz waves, spanning the millimeter and submillimeter wavelength ranges between the microwave and far-infrared regions (approximately 3 mm to 30 μm), represent a critical spectral range in astrophysical and cosmological research. Of the photons detectable since the beginning of the universe, approximately 98% fall within the terahertz and far-infrared bands. A significant proportion of these photons originate from the cosmic microwave background radiation, while others arise from excited molecules that exhibit bright spectral emissions in the terahertz range. As a result, terahertz-based astronomical observation techniques are becoming increasingly essential for investigating the universe’s fundamental properties. Through the observation of interstellar atoms, molecules, and dust, terahertz astronomy provides valuable insights into the internal conditions of the interstellar medium and offers a unique observational window into the formation and evolution of stars, planets, galaxies, and the universe itself. In recent years, many large astronomical telescopes have begun incorporating terahertz detectors based on microwave kinetic inductance detector (MKID), positioning MKID as a pivotal technology in the field of terahertz astronomical detection. This paper outlines the fundamental principles of MKID, reviews recent advancements in the application of MKIDs to terahertz detection, and discusses future developments in this promising area of research.

Adding the vortex factors to the Gaussian, Lorenz, and Voigt airglow (aurora) light spectrum profiles of the for the upper atmospheric wind measurement, the vortex expressions of the three profiles of airglow (aurora) light sources are derived theoretically. The three profiles of airglow (aurora) with vortex light are simulated, and it is found that the extinction of the three profiles of light sources varies with the topological charge number l. The Gaussian vortex light rotates around the axis and the phase changes by 2πl, and the central extinction part and phase increase with the increase of l. The main extinction direction of Lorenz vortex is the transverse axis distribution direction. With the increase of l, the light intensity decreases, and the center extinction is carried out in discontinuous mode, which has a spiral spatial phase structure. Voigt vortex light profile is symmetrical on both the transverse and longitudinal sides, and the top is V-shaped extinction along the -z direction. The expressions are derived between the interference intensity of the three profile of vortex light, optical path difference and topological charge number, and the 3D diagram of the interference fringe of the three profiles of vortex light is simulated, and it is found that the spatial spectral intensity produces different fork structures under different topological charge number: with the change of vortex phase, the original spatial distribution changes, and the whole extends and extrudes from the maximum light intensity to both sides, and the influence of vortex phase extrude and dislocation is greater under fractional topological load. The experimental results show that there are fringes outside the bright ring of the Gaussian vortex light with the same topological charge number l, and the total topological phase will increase 2π and the beam waist radius will increase with each increase of topological charge number l by 1.

Radionuclides have been widely used in the fields of nuclear medicine, nuclear security and non-destructive testing, and their accurate identification is the basis of qualitative detection of radionuclides. In the portable nuclide recognition instrument, the traditional energy spectrum analysis method has the shortcomings of high delay and low recognition rate. This paper proposes a lightweight neural network model for nuclide recognition based on kernel pulse peak sequence and its FPGA hardware acceleration method. A lightweight and efficient neural network model is constructed by introducing depth-separable convolution and reciprocal residual modules, and using global average pooling to replace the traditional fully connected layer. For the network training data set, NaI (Tl) detector model was constructed through Monte Carlo toolkit Geant4 to obtain the analog energy spectrum, and then a simulator generated nuclear pulse signal sequences according to the energy spectrum, and 16 kinds of nuclear pulse signal data were constructed. Finally, the trained model is deployed to PYNQ-Z2 heterogeneous chip through optimization methods such as quantization, fusion and parallel computing to achieve acceleration. Experimental results show that the recognition accuracy of the proposed model can reach 98.3%, which is 13.2% higher than that of the traditional convolutional neural network model, and the number of parameters is only 2 128. After FPGA optimization and acceleration, the single recognition time is 0.273 ms, and the power consumption is 1.94 W.

Ionic liquid ion sources have the capability of generating diverse heavy molecular ions, and their applications have been investigated in the field of ion thrusters. This study aims to determine the quality parameters of ionic liquid ion beams and establish methods for their control. Firstly, the beam acceleration process in an ionic liquid ion source was simulated using Particle-in-Cell (PIC) simulation methods, and the effects of the beam current, acceleration voltage, and emitter-extraction gap on the beam emittance and Twiss parameters were investigated. The results indicate that the normalized emittance decreases with a reduction in the beam current and emitter-extraction gap, as well as with an increase in the acceleration voltage. The kinetic energy broadens during the acceleration process. The acceleration efficiency is not obviously affected by the beam current or acceleration voltage. However, it increases with the expansion of the emitter-extraction gap. Secondly, the control of a centimeter-scale beam was simulated by utilizing the beam parameters derived from the simulation of the acceleration process. The results demonstrate that the divergence, velocity distribution, and specific impulse can be controlled by a set of three-electrode electrostatic lenses without imposing additional demands on the power source on the ionic liquid electric thruster.

To address the issue of system-level electromagnetic compatibility, a new method of predicting electromagnetic interference of complex systems based on artificial neural network (ANN) reverse model is proposed in this paper. Firstly, the electric field radiated emission (RE) of single equipment is measured. The training data of system-level RE are obtained by simulation based on the equivalence principle of radiated emission. Frequency, RE and coordinate of each single equipment are selected as the input variables, and the system-level RE is the output variable. A reverse model of the three-layer back-propagation (BP) ANN with Levenberg-Marquardt (LM) algorithm is established by exchanging the input–output variables. The alternative ANN with minimum validation error is searched as the ultimate ANN. The numerical root-finding algorithm (regular-falsi method and conjugate gradient method) are adopted to calculate the RE of multi equipments. The results show that the validation error of this reverse model is significantly improved compared to the traditional three-layer LM-BP ANN. Especially, the ANN reverse model based on conjugate gradient method reduces the validation error from 0.4159% to 0.0997%. This method is independent of complex ANN structures, and improves simulation accuracy with limited training data, which provides a new efficient and feasible solution for electromagnetic compatibility evaluation of electronic information platforms such as ships, satellites, and aircrafts.

In view of the adverse effect of noise on frequency hopping signal parameter estimation, a frequency hopping signal parameter estimation method based on time-frequency transform and waveform shaping is proposed. The time-frequency ridge is calculated by the short-time Fourier transform of the frequency hopping signal, the waveform shaping of the time-frequency ridge is processed to eliminate the false time-hopping interference caused by noise, and the hopping period sequence is obtained through the time-hopping sequence. The histogram of the hopping period sequence is calculated, and the value with the most occurrence times is selected to calculate the hopping speed of the frequency hopping signal. According to the hopping period sequence, signal of each hop is extracted respectively, and then the frequency is estimated. The effectiveness of the proposed method is verified by experiments, and the ideal estimation results of hopping time, hopping speed and frequency of frequency hopping signal under low signal-to-noise ratio are guaranteed by comprehensive use of time-frequency transformation and waveform shaping technology.

Aiming at the displacement measurement problem of two-dimensional high-frequency motion of two-axis piezoelectric shear stacks driven by high-frequency voltage, a method for measuring the displacement of piezoelectric shear stacks by using the machining trajectories of atomic force microscope (AFM) probe in tapping mode was proposed. Firstly, the thermoplastic polymer polymethyl methacrylate (PMMA) film was prepared, and then the AFM probe tapping experiment was carried out. By scanning the processing trajectory of the AFM probe and post-processing it, the two-dimensional high-frequency motion displacement of the piezoelectric shear stack was successfully obtained. Accurate detection of two-dimensional high-frequency complex motion of piezoelectric shear stacks in a semi-contact manner is realized. Based on the experimental data, the variation of the two-dimensional motion displacement of the piezoelectric shear stack with the voltage amplitude and frequency is analyzed.

In this paper, to address the problem that the single-object tracking algorithm of Siamese fully convolutional networks cannot extract the high-level semantic features of the object and cannot focus on and learn the channel, spatial and coordinate features of the object at one time, which leads to degradation of the tracking performance and tracking failures when faced with the challenges of the object's deformation, attitude changes, and background interference in a complex scenario, we propose a single-object tracking algorithm for Siamese networks based on the multiple-attention mechanism and response fusion. In this algorithm, three modules, namely, the backbone feature extraction network with small convolutional kernel fused with jump-layer connected features, the improved attention mechanism, and the response fusion operation after convolutional inter-correlation are designed to enhance the tracking performance of this algorithm, and the effectiveness of these three modules is verified by ablation experiments. Finally, after testing on the OTB100 benchmark dataset, the tracking accuracy reaches 0.825, and the tracking success rate reaches 0.618. Meanwhile, compared with other advanced algorithms, it shows that the algorithm not only can effectively cope with the problem of decreasing performance of object tracking algorithms in complex scenarios, but also can further improve the tracking accuracy under the premise of guaranteeing the tracking speed.

Scatter-shift ghost imaging edge extraction methods require multiple sampling of the object to obtain a high quality edge map. To solve the problem of many samples and long time when extracting the edge of the object by scatter-shift ghost imaging, convolutional neural network is adopted to the edge extraction experiment of ghost imaging. Firstly, the unknown image is irradiated by Walsh scattering, the sampled signal collected by the barrel detector is input to the ghost imaging edge extraction network as the image feature information, finally the edge information map of the detected object is directly outputted by the trained network, and the output of the convolutional neural network is optimized by using the non-maximum value suppression algorithm. The experimental results show that for the reconstructed object of 128×128 pixels, the signal-to-noise ratio and structural similarity index of the ghost imaging edge extraction network output edge pattern are 5 times and 2 times higher than that of the scatter-shift ghost imaging respectively when the sampling number is 1600, which successfully improves the quality of the ghost imaging edge extraction under the low sampling rate and reduces the sampling time. The ghost imaging edge extraction scheme using convolutional neural network is conducive to fast and high-quality edge detection of ghost imaging in practical applications of object recognition and security inspection.

In recent years, the field of quantum information technology has experienced rapid growth, with a particular focus on electromagnetic sensors that utilize Rydberg atoms. Rydberg atoms, characterized by their high energy states, have garnered significant attention due to their highly sensitive response to external fields. These atoms offer several advantages, including self-calibration capabilities and direct traceability to the International System of Units (SI), which make them exceptionally suitable for applications in radio sensing and detection. Since Shaffer and others made a breakthrough in measuring microwave electric field intensity using the electromagnetic induced transparency effect of Rydberg atoms in 2012, the sensitivity and uncertainty of measuring microwave electric field intensity have significantly surpassed those of traditional microwave measurement results. Over the past decade, research centered around new theories and technologies, such as Rydberg atom superheterodyne technology, has enabled the measurement of electromagnetic wave frequency, polarization, phase, amplitude, and other parameters. Related engineering technologies are also experiencing significant growth, expected to have a disruptive impact on traditional radio technology. This comprehensive review aims to summarize the research progress in the field of Rydberg atom-based radio technology over the past ten years. It will start by examining the underlying principles of detection and then proceed to outline the developmental trajectory of this domain. Finally, the review will provide insights into the future trends and potential directions for the evolution of this technology.

The far-field phase inversion exhibits degeneracy states, leading to the problem of encountering multiple solutions when recovering the wavefront. In comparison to traditional iterative algorithms, the combination of phase modulation and deep learning in the phase inversion method not only significantly reduces computational complexity but also effectively solves multi-solution problems. This method possesses strong real-time capabilities and a simple structure, showcasing its unique advantages. In this paper, different Walsh functions are used to modulate the phase, and a deep learning approach is taken to train a convolutional neural network to obtain the 4th-30th order Zernike coefficients from the modulated single-frame far-field intensity maps so as to recover the original wavefront, which solves the problem of multiple solutions of phase inversion. For the residual wavefront of the turbulent aberration of 3-15 cm atmospheric coherence length, the ratio of its RMS to the RMS of the original wavefront can reach 7.8%. In addition, this paper also deeply investigates the effects of various factors such as Zernike order, random noise, occlusion, and intensity map resolution on the wavefront recovery accuracy. The results show that this deep learning-based phase inversion method exhibits good robustness in complex environment.

To estimate the aircraft pose in complex situation, this paper proposes a new method of aircraft pose estimation based on neural network line extraction. This method uses 3D model to render images, and forms dataset through adding backgrounds. The dataset is enhanced to make the algorithm robust. The line extraction model uses convolutional neural network to extract deep features, and uses heatmap to obtain aircraft feature lines. The target pose is solved by combining the aircraft feature line, the aircraft 3D model and the perspective-n-line method. The accuracy of the line extraction model is 91% in complex background. The accuracy is 84% after addingall sorts of noises. The aircraft pose is solved by using EPnL algorithm and nonlinear optimization. The average angle error is about 0.57°, and the average translation error is about 0.47% when the target is in a complex background. After addingall sorts of noises to the image, the average angle error is about 2.11°, and the average translation error is about 0.93%. The aircraft pose estimation method proposed in this article can accurately predict the aircraft pose under complex backgrounds and various types of noise, and its application scenarios are more extensive.

To improve the radiation measurement efficiency of nuclear retirement facilities and reduce the risk of radiation exposure to measurement personnel, a radiation patrol control system for multiple unmanned vehicle formations has been designed. Firstly, the navigation following formation strategy is adopted to control the robots to move in a predetermined formation, while collecting real-time radiation intensity information and their respective position data measured by each unmanned vehicle during the formation process, to preliminarily analyze the radiation distribution inside the environment. Secondly, utilizing radiation intensity and location information, the Markov chain Monte Carlo method is employed to estimate the parameters of the radiation source. The simulation results show that the unmanned vehicle formation can move along the automatically planned path in radiation environment, with advantages such as fast response speed, high control accuracy, and it can estimate the parameters of the radiation source position coordinates.

This article employs Fourier transform infrared spectroscopy to investigate radiometric calibration methods and the measurement of continuous atmospheric transmittance across the shortwave infrared band. The presence of multiple strong absorption bands within the shortwave infrared spectrum (0.9-2.2 μm) leads to significant errors in the commonly used Langley method, and even the improved Langley method struggles to yield accurate results for the calibration of these strong absorption bands. To fulfill the high-precision measurement demands for atmospheric transmittance across the entire shortwave infrared band, this paper introduces an enhanced method for calculating atmospheric transmittance. Initially, the Langley calibration technique is utilized to determine the instrument calibration value and response function K in the non-absorption band. Subsequently, the instrument response function in the absorption band is derived by interpolating the wavelength based on the instrument response function calibrated in the non-absorption band. Ultimately, the instrument calibration value is established by correlating it with the solar irradiance at the atmosphere’s top, thereby obtaining the atmospheric transmittance across the entire shortwave infrared band. Compared to results calculated by the medium-resolution atmospheric radiative transfer model software CART, the atmospheric transmittance values obtained using this method within the 0.9-2.2 μm band exhibit an average error of less than 2.5%.

In a complex electromagnetic environment, magnetic field interference is one of the main reasons for the error of fiber optic gyroscopes. To reduce the influence of the magnetic field generated by the heating plate in the body of the fiber optic gyroscope on the accuracy of the gyroscope, a double-layer heating plate structure is designed, and a comparative analysis of the magnetic field at the fiber optic ring position above the single-layer and double-layer heating plates is carried out by using the finite element method, and the influence of the magnetic field on the accuracy of the fiber optic gyroscope is calculated based on the analysis results. The results show that the magnetic field of both heating plates is non-uniform at the location of the fiber optic ring. The magnetic flux density near the fiber optic ring to the heating plate has a ring-like distribution, while the magnetic flux density away from the heating plate has a strong center and weak center distribution. With the increase in the distance between the fiber ring plane and the heating plate, the maximum magnetic flux density of the single-layer heating plate on the fiber ring plane is about 30 to 122 times that of the double-layer heating plate. The magnetic sensitivity phase error of the fiber optic gyroscope varies sinusoidally with the direction of the magnetic field and the angle between the fiber ring. The phase errors of the magnetic field on the lower surface of the fiber ring are 1.299×10-10 rad and 5.572×10-12 rad, respectively. The above results prove that the magnetic field of the double-layer heating plate interferes with the fiber-optic gyroscope much less than that of the single-layer heating plate and that the electromagnetic interference generated by the double-layer heating plate is much smaller, which is more conducive to improving the accuracy of the fiber-optic gyroscope.

To solve the heat dissipation problem of high heat flux density solid-state laser, a set of micro-compact embedded manifold S-shaped microchannel heat sink was developed using the MEMS technology and the microchannel/heat source co-design method. The heat exchanger uses continuous S-shaped microchannels and the manifold is used to form tiered and segmented flow. Experiment was conducted, using HFE-7100 as the cooling medium. Results show that the heat sink can dissipate 625 W/cm2, with a local maximum temperature of less than 100 ℃ and an average temperature rise of less than 45 ℃. Compared with the traditional manifold rectangular microchannel heat sink, the heat dissipation performance of S-shaped microchannel increased by 12%, but the flow resistance increased by about 56%. Numerical simulation methods were used to evaluate the structural parameters of the S-shaped microchannel heat sink’s heat dissipation ability and flow resistance by changing the amplitude and wavelength of the S shape according to the average temperature of the heating surface, average Nusselt number of the heat transfer surface, pressure drop, and comprehensive performance factor, to find the optimal structure design parameter combination of the S-shaped microchannel. The results show that the comprehensive performance factor of the heat sink has an optimal value under a specific S-shaped configuration, which will be used in subsequent studies.

Due to the less information of distant target, it is always challenging to accurately track the target in the task of infrared dim small target tracking. To improve the accuracy, based on correlation filtering framework, the side window filtering method which can extract the edge features of small infrared target is introduced, and an algorithm of distant target tracking is proposed. Specifically, the side window filtering method is used to process the searching area of the current target, this method could restrain the negative influence of background edge on dim small target location. Next, the correlation filters tracking model is constructed with temporal and spatial regularities to achieve accurate target tracking. To verify the performance of the proposed algorithm, six groups of real infrared dim small target image sequences were used for experiments, and the algorithm is compared with other typical algorithms such as KCF, SRDCF and STRCF. The experimental results show that the algorithm could effectively solve the problems of fast motion, low resolution and strong light background in infrared dim small target tracking tasks, getting higher accuracy with image sequences and complex background.

A composite device of intelligent multifunctional laser protection goggles and automatic detection and alarm is designed and developed, which is mainly used for protection and early warning of human eye damage caused by laser radiation. The protection spectacles, detection and alarm system and intelligent composite protective technology are studied. The laser protection and detection and alarm performance of the composite device are tested. The signal interconnection and linkage between the protection spectacles and alarm device are used to combine the protection spectacles’ double spectacles and send alarm signals. The results show that when the laser protection alarm compound device detects the laser irriadiation, it can send out various alarm signals and compound protection response in different ways, including flashing lights of different colors, sound and vibration alarms, and drive the two protection spectacles to recombine. It can effectively protect human eyes from laser of specific wavelengths (532 nm, 1 064 nm, 470 nm, 808 nm and 700-2 000 nm) as well as from supercontinuum laser, and realize cluster linkage alarm and protection through wireless signal interconnection. The laser protection spectacles and detection and alarm composite device has the characteristics of intelligent, modular and multifunctional integration, and its performance meets the design requirements

Optical elements are the core components of laser systems, and their health status is the key to the stable operation of laser systems. How to realize real-time monitoring and fault diagnosis of optical elements in the working status of laser systems is a problem that urgently needs to be solved in this professional field. To solve this problem, this paper proposes a fault diagnosis method for optical elements based on infrared and visible light videos. Firstly, a long-wave infrared camera and a visible light camera are used to collect video information during the working process of the optical element. Then, the collected video information is processed using anomaly point detection algorithms. Finally, the fault diagnosis and localization of the optical element are carried out in combination with the thermal rise characteristics of the optical element. The experimental results show that, under the same algorithm, the method proposed in this paper has improved the fault diagnosis precision rate, false alarm rate and missed alarm rate by 9.70%, 3.60% and 6.10%, respectively, compared with the method of fault diagnosis using infrared videos alone; the method proposed in this paper has improved the fault diagnosis precision rate, false alarm rate and missed alarm rate by 18.00%, 16.00% and 2.00%, respectively, compared with the method of fault diagnosis using visible light videos alone.

During the flight of hypersonic vehicle, plasma sheath will be produced on the surface due to the influence of surface shockwave. Because the plasma sheath will absorb, reflect and scatter electromagnetic waves, the communication signal will be attenuated or even interrupted, causing “blackout” problem. Theoretically, the interaction between the plasma sheath and microwave is nonlinearly changing with electric field, so there may be a suitable E-field amplitude and irradiation time interval to make electromagnetic wave transmissivity rise. For this possibility, Finite Element Analysis is used to conduct a two-dimensional coupled simulation of the plasma sheath flow field and the electromagnetic field on the hypersonic vehicle’s surface, and the change of the plasma sheath transmissivity after microwave irradiation is obtained. The plasma sheath was irradiated for 30 ns with electric field of 5×104 V/m, 1×105 V/m, 2.5×105 V/m, 5×105 V/m, respectively. The maximum transmissivity to 1.2 GHz and 1.6 GHz electromagnetic waves is enhanced after irradiation. It provides a new possibility to solve the “blackout” problem.

Utilizing the muzzle voltage of the electromagnetic railgun, the contact resistance between the sliding armature and the copper rail surface during the launch process can be calculated to analyze the contact characteristics. However, the muzzle voltage signal contains a large amplitude of reverse induced electromotive force due to the complex augmented rails structure of the launcher. Meanwhile, the firing sequence of the pulse forming network disturb the detected muzzle voltage signal as system noise interference. Therefore, it is difficult to accurately calculate the contact resistance. To solve this problem, a noise suppression method of muzzle voltage system based on VMD-OptShrink is creatively utilized to suppress jagged noise. In this method, variational mode decomposition (VMD) can decompose the muzzle voltage signal in time-frequency domain according to the frequency characteristics. Then OptShrink is used to extract the low-rank components of the decomposed signal to obtain the denoised muzzle voltage. Finally, the contact resistance is calculated to analyze the armature-rail contact characteristics. The test results show that this method can suppress the muzzle voltage system noise well. The calculated armature-rail contact resistance waveform is smooth, which is conducive to the analysis of the armature-rail contact characteristics. The armature-rail contact resistance decreases rapidly at the initial stage of launching, then it fluctuates slowly until the armature slides out of the muzzle and the contact resistance increases sharply. The method proposed in this paper provides a new and reliable reference for the launching performance monitoring of electromagnetic railgun.

With the frequent appearance of UAVs in several recent local wars and armed conflicts, the study of UAV detection and tracking technology has become a research hotspot in imagery and other fields. Due to the characteristics of low altitude UAV targets such as large mobility, small size, low contrast and complex background, their capture and tracking is a major challenge in the field of photoelectric detection. To address these difficulties, this paper proposes a real-time long tracking method based on YOLOv5 and CSRT algorithm optimization to achieve stable tracking of UAVs in clear sky, urban and forest scenes. First, two capture networks with different resolutions are established for different stages of tracking, and the two networks are optimized for small target detection and performance optimization respectively, and positive and negative samples are added to the UAV data set according to its characteristics to achieve data enhancement. Then, the CSRT algorithm is optimized using GPU and combined with feature point extraction to construct a low-altitude UAV detection and tracking model. Finally, the algorithm is deployed using Tensorrt and experimented on a self-built dataset. The experimental results show that the proposed method achieves a tracking performance of 400FPS on RTX 2080Ti and 70FPS on NVIDIA Jetson NX. Stable long-time tracking is also achieved in real field experiments.

To solve the problem that “cat’s eye” target is difficult to recognize at night, a contour matching algorithm based on normalized central moment is proposed. Firstly, the median filter is used to denoise the image, and the fixed threshold segmentation is used to complete the image segmentation, so that the “cat’s eye” target is separated from part of the background. Roberts edge detection is used to extract the edges of all targets. Finally, the contour matching algorithm based on the normalized central moment is adopted, which is not affected by translation and contraction. All the circular targets in the image are extracted, and the real targets are identified by area discrimination. The minimum peripheral circle is drawn for the identified targets, and the coordinates of the center of the circle are used to locate them. The feasibility of this method is verified by experiments and comparisons of “cat’s eye” images under different illumination intensities, and the effectiveness of this method is verified by target recognition evaluation index. Experimental results show that the global accuracy of this method can reach 92.1%, and it can successfully identify the “cat’s eye” target under different illumination intensity at night.

For broadband communication signal detection problem, as the current signal detection algorithm based on deep learning is not suitable for dealing with large bandwidth and large wide broadband signals, and there is the inherent deviation in signal frequency parameter estimation, we put forward intelligent broadband communication signal detection algorithm based on spectrum decomposition, thus to complete highly accurate detection of narrow-band signal in large bandwidth receiving signal. First, the broadband signal is transformed into a grayscale time-frequency spectrum which is subsequently decomposed into a sub-spectrum suitable for the input size of the target detection network. Then, the anchor-free YOLOx target detection algorithm is used to detect the narrowband signal targets in the sub-spectrum. Finally, the signal detection results of the sub-spectrum are fused to obtain the detection results of the time-frequency parameters of the narrow-band signal. Experimental results show that the proposed algorithm can adapt to the complex noise environment. Compared with other deep learning algorithms and traditional energy detection algorithms, the proposed algorithm has higher signal detection accuracy, lower false alarm probability, smaller average error of signal parameter estimation, and stronger robustness, practicability and versatility.

The phase information of the transmitted object, also known as digital holography, can be obtained by the element interference based on prism pair. This method has the advantages of compact structure, stable interference fringe and high measurement accuracy. In this paper, the ray tracing method is used to establish the equivalent model of ray tracing, considering the azimuth rotation of the prism pair and the eccentricity of the inclined plane. The equivalent model is used to simulate the digital holographic interference fringes, and give the analytic expressions of fringe density change and tilt. The interference digital holograms are obtained and the refractive index distribution is inversed for the micro structure optical elements such as single-mode and multimode fibers. The experimental device of micro imaging unit interference is built, and the actual measurement interference pattern is obtained. The experimental results are consistent with the simulation results, which proves the effectiveness of this model.

Atmospheric neutrons can cause the single event effect (SEE) of integrated circuits, resulting in data loss or functional interrupt. The SEE failure rate caused by atmospheric neutrons depends on its flux, thus obtaining the atmospheric neutron flux is the premise of SEE failure rate assessment. In this paper, the atmospheric neutron energy spectra and fluxes in Guangzhou, Lanzhou and Lhasa are measured using the Bonner sphere spectrometers (BSS). Typical characteristics of atmospheric neutron spectrum are obtained. The measured results show that the atmospheric neutron flux in different areas is affected by the altitude, and the terrestrial atmospheric neutron flux increases with the altitude. In addition, the nuclear reaction process of primary cosmic ray particles in the earth’s atmosphere can also be simulated based on the Monte Carlo simulation tools, so as to calculate the atmospheric neutron spectrum. It shows that the measured data of atmospheric neutron spectra are in good agreement with the simulation data. These data can be used in quantitative evaluation of atmospheric neutron-induced SEE of integrated circuits.

To explore the influencing factors of the pulsed electric field on the prevention and control of aquatic organism fouling, and to determine the minimum electric field conditions required for effective prevention and control of fouling organisms, we built a pulsed electric field test platform. Approximate square wave pulses were generated by the pulse forming network. During the experiment, we recorded the death rate and morphological structure changes of the Daphnia magna. With the help of Matlab nonlinear fitting, we obtained the functional relationship between the pulsed electric field-induced death rate and the electric field strength, the total equivalent processing time, and the pulse injection energy density. The paper takes a main canal project as an example to introduce the principle of parameter selection and platform construction method of pulsed electric field for controlling large water fleas. The results showed that the treatment effect of the pulsed electric field on the Daphnia magna is positively correlated with the electric field strength, the total equivalent treatment time and the pulse injection energy density. When the electric field strength is between 0.5 and 1.5 kV/cm, the induced mortality increases by about 35% for every 0.5 kV/cm increase in the electric field strength. When the electric field strength is higher than 2.0 kV/cm, the total equivalent processing time is higher than 900 μs, or the pulse injection energy density is higher than 80 J/L, the pulsed electric field can produce more than 80% induced mortality.

The key parameters of the neutral beam, such as beam uniformity and beam divergence angle, can be obtained by analyzing the infrared images generated by the beam bombarding the target surface. Due to the camera setup angle, the IR images show geometric distortion, which affects the accurate analysis of the beam parameters. Therefore, so the images should be corrected for the distortion. The traditional Hough transform, canny lines algorithm, and probabilistic Hough transform methods are not effective in detecting straight lines on this image, and there is a problem of detecting discontinuous and incorrect line segments. In this paper, Sobel filter is used to sharpen the infrared image in the horizontal and vertical directions respectively and line segment feature is detected by line segment detector (LSD) algorithm. Then complete straight lines are obtained in the image by clustering and fitting the line segments according to the geometric and angular relationships between them. Vanishing points is calculated by the intersection points of the lines. Finally, the corrected image is obtained based on the perspective relationship. Experiment results prove that this method can achieve automatic and effective correction of neutral beam infrared images and it lays a basis for obtaining key parameters of the beam.

A new idea of adjusting half-power beam width is applied to design a navigation antenna of Beidou-2 B3 band, which can realize beam width transformation and apply to different beam forming scenes. The microstrip patch array is modeled in HFSS simulation software. On the basis of keeping the right-handed circular polarization, the half-power beam width can be reduced or expanded without changing the structure of the array, the directional beam forming and wide beam forming with adjustable main lobe direction can be realized to cope with different working environments, and the directional anti-interference ability can be achieved. The simulation results show that the maximum gain of directional beam forming and wide beam forming at B3 center frequency is about 7.13 dBi and 3.56 dBi, the half-power beam width is 52° and 119° respectively, and the axial ratio width in xOz plane is 90° and 166° respectively. In B3 frequency band, the reflection coefficient of each feeding port is under -11 dB, and the isolation degree of adjacent ports is under -28 dB. The designed navigation antenna with adjustable beam forming mode is suitable for working scenes that often switch between open space without shielding and specific shielding environment, and it can improve the low gain of traditional mobile navigation terminal in the environment of high shielding angle such as “Canyon City”.

In recent years, with the advancement in the field of biomedical applications, atmospheric pressure non-thermal plasma technology has shown many advantages in disinfection and sterilization. In terms of its application, the key lies in how to easily generate a large-area, uniform and stable plasma. In this work, a set of unipolar microsecond pulse array plasma jet system is developed, which can be excited to generate plasma jet under atmospheric pressure and realize large-area sterilization treatment. The system generates high-voltage pulses with a peak voltage of 20 kV and a frequency of 15 kHz. The jet is uniform and stable, covering an area of 37.7 cm2, the jet length is stable at 6 cm and the jet power is 40.05 W. Treating for 5 min can basically inactivate all Bacillus subtilis spores in the area covered by the jet. The effects of different parameters on the sterilization efficiency are investigated, and the results show that the sterilization rate is positively correlated with the working voltage, pulse frequency and treatment time. The sterilization effect is better in helium atmosphere. The SEM images show that the plasma jet damaged the shell structure of Bacillus subtilis spores, hence the spores failed to metabolize normally and eventually died.

The gain of silicon photomultiplier tube will drift greatly due to temperature variation, which will affect the gain accuracy of silicon photomultiplier tube. To realize that silicon photomultiplier tube gain does not change greatly with temperature variation, an automatic gain correction system for silicon photomultiplier tube is designed, including the design of a high voltage power supply and an acquisition system based on single chip microcomputer.The high voltage module can accurately operate in the temperature range of -10 ℃ to 60 ℃, and the power noise is about 30 mV, which can meet the requirements of silicon photomultiplier tube performance testing.Through frequency sweep test and laser irradiation test, the acquisition system can better pass the 60 MHz AC signal, and transform the optical signal into a more obvious electrical signal.The system provides a working voltage and acquisition circuit to Jingbon Compony’s silicon photomultiplier tube array JARY-TP3050-8X8C.

The use of aluminum alloy high-voltage wire harnesses instead of copper wire harnesses can reduce the weight of electric vehicles, increase battery endurance, and reduce cost. Aiming at the difficulty of reliable and effective connection between aluminum alloy high-voltage wire harness and copper alloy terminal, this paper proposes to use electromagnetic pulse crimping technology (EMPC) to connect aluminum alloy high-voltage wire harness and copper alloy terminal. A set of EMPC device suitable for the connection has been developed. The EMPW device has a maximum discharge energy of 28 kJ. During the crimping process, with the increase of the discharge voltage, the temperature of the terminal surface increases. The aluminum alloy high-voltage wire harness and the copper alloy terminal can be connected reliably at 12 kV. An optical microscope was used to analyze the microstructure of the connection interface, and the electrical and mechanical properties of the interface were tested. The analysis shows that the electromagnetic pulse crimping technology can realize metallurgical combination between the aluminum alloy high-voltage wire harness and the terminal as well as the aluminum alloy core wires. The connection interface has a corrugated morphology and a vortex morphology. The test results show that the contact resistance, vibration test and tensile load test of the joint meet the industrial standards of automobile and the national standards of cable joint.

A photonic crystal fiber refractive index (RI) sensor based on enhanced surface plasmon resonance (SPR) effect is proposed. The sensor structure is spliced with a photonic crystal fiber (PCF) by a fiber fusion splicer, so that an air hole is introduced in the middle of the photonic crystal fiber to form a PCF-air hole-PCF optical fiber sensing structure. Then, a thin gold film is deposited on its surface by using magnetron sputtering coating process. Experiments are carried out to investigate the response of the refractive index and temperature of the sensor. The results show that in the refractive index (RI) range of 1.333-1.389, the sensor has an average RI sensitivity of 2 142.52 nm, with a linearity of 0.981 and a quality factor about 13.10. Experimental results show that the sensor is not sensitive to temperature. Compared with the PCF sensing structure without air hole, the air hole introduced enhances the SPR effect, so that the sensor has a good resonance peak depth. Benefiting from the above advantages, this type of sensor is expected to be applied in fields such as biomedicine and environmental monitoring.

We present a formula to directly obtain the final relative energy spread of a trailing beam at the maximal acceleration distance. The formula works for electron beams in a two-bunch plasma wakefield acceleration stage in the so-called nonlinear bubble regime. It only requires the longitudinal profile of the trailing beam and the longitudinal wakefield within the trailing beam at the beginning of an acceleration. This formula not only works well for drive beams and trailing beams with the same initial energies, but is also available for those beams with different initial energies. We find that the relative energy spread of the trailing beam obtained from the formula is determined by the ratio of the trailing beam’s initial energy to the drive beam’s initial energy rather than the specific value of their initial energies. We perform several computational simulations using the quasi-static particle-in-cell code QuickPIC, and the results agree well with that calculated from the formula.

Two atmospheric pressure microwave plasma jet (MW-APPJ) devices with different nozzle structures are designed which are based on the coaxial transmission line structure. The frequency is 2.45 GHz and working gas is argon. What's more, the effects of two different nozzle structures on the characteristics of plasma discharge have been studied. Based on the electromagnetic field simulation results, the MW-APPJ generates a high-intensity electric field at the nozzle. After optimizing the structure, the field strength at the nozzle have reached the breakdown field strength required for argon ionization under the frequency of 2.45 GHz. Meanwhile, the simulation of the argon flow distribution was carried out under steady-state using multi-physics coupling simulation software. In addition, the basic characteristics of the atmospheric pressure argon plasma jet under the two nozzle structures were compared and analyzed through experiments. The experimental results show that different nozzle structures can affect the variation of reflection parameter with input power, but do not affect the variation of plasma jet length with input power and the variation of reflected power with inlet flow; at the same time, under atmospheric pressure, the steady-state microwave plasma jet exhibits metal-like property and the electrons in the plasma can only absorb microwave energy in a very thin area, which causes large reflected power of the microwave.

Evaluation function of automatic focusing system is the key to evaluate image quality. In multi-depth-of-field scenarios, when the target is located in the center of the image, the sensitivity of the traditional focusing evaluation curve is low; when the target deviates from the center, the focus evaluation function curve is prone to local maximum, which affects the accuracy of the automatic focusing system. In view of these two situations, this paper proposes a method based on U-Net neural network and sets the corresponding window and evaluation function. When the object is located in the center of the image, a new focusing evaluation function, SMD-Roberts function, is proposed. When the target is not in the center of the image, the corresponding window is set for the image and the SML evaluation function is selected to evaluate the image quality. Experimental results show that , compared with traditional focused evaluation function and central window method, this method can effectively solve the problem that the focus evaluation function is not accurate in judging the clearest position of the object and the double peak of the focusing evaluation function curve in multi-depth-of-field scenes and obviously improve the unbiasedness, unimodal and sensitivity of the focused evaluation function. This method has strong universality and is more suitable for focused evaluation system.

The single-pixel imaging system is a computational optical imaging technology that obtains the two-dimensional distribution information of the target through a single-pixel detector without spatial resolution. Compared with traditional direct imaging technology, it has a series of advantages such as high energy collection efficiency and high sensitivity. In the field of high-energy physical diagnosis technology it has broad application prospects. Aiming at the problem that the actual single-pixel compressed sensing imaging system has large reconstruction noise in complex diagnostic environments, this paper proposes and implements a single-pixel imaging system based on the block smooth projection Landweber quadratic reconstruction algorithm. According to the distribution characteristics of the algorithm's observation matrix and the digital micromirror hardware input requirements, the transformation of the actual projection observation matrix is realized, and the simulation analysis and experimental test of the single-pixel diagnosis are realized by using the quadratic reconstruction algorithm. The simulation results show that under the condition of a 20% to 30% sampling rate, the peak signal-to-noise ratio of the reconstructed image is greater than 20 dB, and the structural similarity is higher than 0.8. The single-pixel imaging platform is further built to complete the experimental research and verification. The experimental results show that the recovery effect of the target scene using the quadratic reconstruction algorithm model is better than the other two traditional algorithms. The quadratic reconstruction single-pixel imaging system can reconstruct a clear original image with a sampling rate of only 20%, and has good noise suppression characteristics.

Aiming at the insufficient stiffness of the bonnet polishing system of the six-degree-of-freedom tandem joint robot, which may cause vibration and further mid-spatial-frequency errors, used we the IRB 6700 robot as the research object, established the modal analysis model based on Ansys Workbench and combined experiment to analyze the dynamic characteristics of the robot bonnet polishing system in the working condition frequency range. The experimental and simulation results together show that the robot bonnet polishing system has at least 5 modes in the working condition frequency range, and the jitter amplitude at the end of the robot is millimeter-level when the resonance occurs. Robot processing is severely restricted. In addition, for the application of advanced optical component polishing technology in the robotic bonnet polishing system, a vibration suppression bonnet tool was designed, and the fixed-point polishing and whole-surface polishing comparison experiments were carried out with the ordinary bonnet tool. The results show that the RMS and spectral amplitude of the fixed-point polishing spot of the vibration suppression bonnet are generally lower than that of the ordinary bonnet, and the introduced mid-spatial-frequency errors PSD is 40% lower than that of general bonnet polishing.

There are many factors that affect the measurement accuracy of binocular vision system. Currently, the influence of system structure parameters on the measurement accuracy mainly includes the angle between optical axis and baseline, baseline distance, horizontal viewing angle, object distance and lens focal length. Since the aperture size directly affect the imaging resolution, it is the core factor that determines the accuracy of binocular vision measurement. Consequently, according to the incoherent imaging theory, the binocular imaging process is simulated and tested. Moreover, Speeded Up Robust Features algorithm is adopted to extract and match the features of the image pairs to obtain their parallax values. The parallax root mean square error is calculated to represent the systematic errors. The results show that the system error decreases with the increase of lens aperture, and approaches saturation. This research can provide theoretical and experimental basis for the selection of system parameters and aperture size during the design of the binocular system.

Having a new generation of selective laser melting process, surface exposure selective laser melting technology has the advantages of high forming efficiency and uniform temperature field, and is becoming a research focus in additive manufacturing field. The influence of laser spot overlap rate and electric current on the shape accuracy of single-layer laser melting with surface exposure was investigated. The effects of overlap rate, exposure time and electric current on the forming of laser spot, track, circular ring and sharp angle were studied by the control variable method. The experimental results show that: within a certain range, the larger the electric current is, the more uniform the laser spot is, and the more conducive to forming; The lowest shape error can be obtained with overlap rate of 38.4%. The forming error of the circular ring increases with the increase of electric current. The forming error of sharp angle increases first and then decreases with the increase of electric current. The shape error caused by zero-order diffraction can be reduced when the overlap rate is 46.1% and 38.4%.

Surface-enhanced Raman spectroscopy (SERS) technology has been widely used in viral molecular detection due to its high sensitivity, simple operation and rapid detection. The research of virus detection by Raman technology at home and abroad mainly focuses on the detection of the SERS spectrum of viral nucleic acids and various bases that make up the nucleic acids, and detection of viral proteins is rare. In this paper, the S protein of the new coronavirus (SARS-CoV-2) is used as the detection object, and with the label-free SERS detection method, the ordinary Raman spectra of solid and saturated liquid S protein of the SARS-CoV-2 and the SERS spectra of the low-concentration S protein of SARS-CoV-2 on the substrate of gold nanoparticles with a size of 40 nm are compared. The results show that it is completely feasible to use SERS technology to detect the S protein of SARS-CoV-2 on the substrate of 40 nm gold nanoparticles. The carboxyl groups in the S protein molecule of SARS-CoV-2 and gold nanoparticles are molecularly enhanced, and the amino groups and gold nanoparticles are electromagnetically enhanced, so that the Raman effect of the S protein of the SARS-CoV-2 is enhanced and the peak position is moved to a certain extent. The experiments obtained relatively good SERS spectra of the low-concentration S protein of SARS-CoV-2, which provides a method for the establishment of a sensitive, specific and rapid detection technology for the S protein of the SARS-CoV-2.

Disinfection and sterilization technologies are of great significance in the food industry, medical field and water treatment, et al. Compared with traditional chemical and thermal methods, physical disinfection and sterilization approaches such as γ-rays, X-rays, electron beams, microwaves, low-temperature plasmas, ultraviolet rays and high-voltage pulsed electric fields have the advantages of no environmental pollution, low sterilization temperatures, no chemical residues, and so on. These physical disinfection and sterilization approaches are getting increasing concerns because of unique advantages. In this paper, the mechanisms of present physical disinfection and sterilization technics were summarized. The advantages and disadvantages of these physical means as well as their application areas are reviewed. Based on the superiorities and drawbacks of each method, different approaches should be adopted for the disinfection and sterilization of specific objects. Moreover, this paper highlights the trends on development of physical disinfection and sterilization approaches and proposes the extensive demands of the physical approaches on various aspects of our life.