To improve the search efficiency of the unmanned aerial vehicle (UAV) swarm in disaster areas, the target distribution probability graph in the prior information is introduced, and a drone cluster search trajectory planning method based on probability of containment (POC) is proposed. Firstly, based on the concept of probability of containment in search theory, a task area division method for polygonal and circular areas is constructed, and the corresponding search trajectory is constructed. Then, the influence of factors, including probability of containment, probability of detection, and probability of success on search efficiency, is sorted out, and the objective function of search trajectory optimization is constructed. Subsequently, an adaptive mutation operator is used to improve the differential evolution algorithm, thus constructing a trajectory optimization process based on the improved adaptive differential evolution algorithm. Through simulation verification, the proposed method can achieve a full coverage search of the task area and a rapid search within a limited time, and can prioritize the coverage of areas with a high target existence probability as much as possible to achieve a higher cumulative success probability. Moreover, the time efficiency and accuracy of the solution are high.

To weaken or avoid the impact of dynamic threats such as wind and extreme weather on the real-time path of a UAV swarm, a path-planning method based on improved long short-term memory (LSTM) network prediction parameters was constructed. First, models were constructed for wind, static threats, and dynamic threats during the flight of the drone. Then, it was found that atmospheric parameters are typical time series data with spatial correlation. The LSTM network was optimized and used to process time series parameters to construct a network for predicting atmospheric parameters. The state of the drone was adjusted in real time based on the prediction results to mitigate the impact of wind or avoid the threat of extreme weather. Finally, a path optimization method based on an improved LSTM network was constructed. Through simulation, it can be seen that compared to the path that does not consider atmospheric effects, the optimized path has significantly improved flightability and safety.

This letter presents an efficient dipole coupled nanomagnetic logic scheme clocked by voltage-induced stress. The logic signals can be transmitted to an array of eight elliptical nanomagnets in one cycle. Transmission speed is increased 1-2 times versus the conventional stress scheme while the required stress is reduced. Micromagnetic simulations illustrate that both increasing the tilt angleof the electrode pair and decreasing the nanomagnet thickness can reduce the stress. When the nanomagnet thickness is 8 to 12 nm and the tilt angle of the electrode pair is 8° to 10°, it is a tradeoff considering the stress, reliability, and fabrication.

In this paper, we propose a reversal mechanism of magnetic radial vortex core in a Permalloy nanodisk driven by a spin-polarized current injected through a nanocontact. The micromagnetic simulation results indicate that the reversal process of radial vortex core is through the rotation and fusion of an edge soliton pair. Due to the effect of interfacial Dzyaloshinskii–Moriya interaction, the radial chirality and polarity of radial vortex are reversed simultaneously. The transformation is uncovered by detailed studies of magnetization configuration, skyrmion number, energy and effective field. This reversal mechanism of radial vortex differs entirely from the previous mechanisms reported in the literatures. This work not only provides deeper insights into the dynamic properties of magnetic radial vortices, but also has great potential for developing new kinds of spintronic devices using the radial vortices.

In this paper, we propose a performance optimization scheme for all-spin logic device (ASLD); this scheme makes use of asymmetric tunneling layer to overcome the conductivity mismatch problem. Besides, for the material selection of device, this scheme makes advantage of silver as an energy efficient interconnect material to reduce the switching delay. The simulation results indicate that the high spin injection efficiency can be obtained by increasing the thickness of the transmitter-side tunneling layer or decreasing the thickness of the receive-side tunneling layer. Therefore, the structure of asymmetric tunneling layer is expected to be more effective for spin injection. Compared with the traditional interconnect that copper or aluminum is used as a channel material, the time for magnetic moment reversal and the spin current flowing into the output magnet are predicated to be optimized when silver is chosen as the channel material, which can attribute to the fact that the conductivity of silver material is larger, the spin diffusion length is longer, and the spin-orbit interaction is weaker. Meanwhile, when the critical switching current requires for the magnetization reversal is applied, the reliable working length of silver channel is significantly longer than that of copper or aluminum channel. These abovementioned results provide a new method for the performance optimization of ASLD.