As a typical wide bandgap semiconductor, ZnO has received a great deal of attention from researchers because of its strong physicochemical characteristics. During the past few years, great progress has been made in the optoelectronic applications of ZnO, particularly in the photocatalysis and photodetection fields. To enable further improvements in the material’s optoelectronic performance, construction of a variety of ZnO-based composite structures will be essential. In this paper, we review recent progress in the growth of different ZnO–graphene nanocomposite structures. The related band structures and photocatalysis and photoresponse properties of these nanocomposites are discussed. Additionally, specific examples of the materials are included to provide an insight into the common general physical properties and carrier transport characteristics involved in these unique nanocomposite structures. Finally, further directions for the development of ZnO–graphene nanocomposite materials are forecasted.

To address the most significant environmental challenges, the quest for high-performance gas sensing materials is crucial. Among numerous two-dimensional materials, this study investigates the gas-sensitive capabilities of monolayer As, Sb, and Bi materials. To compare the gas detection abilities of these three materials, we employ first-principles calculations to comprehensively study the adsorption behavior of NO and NO₂ gas molecules on the material surfaces. The results indicate that monolayer Bi material exhibits reasonable adsorption distances, substantial adsorption energies, and significant charge transfer for both NO and NO₂ gases. Therefore, among the materials studied, it demonstrates the best gas detection capability. Furthermore, monolayer As and Sb materials exhibit remarkably high capacities for adsorbing NO and NO₂ gas molecules, firmly interacting with the gas molecules. Gas adsorption induces changes in the material’s work function, suggesting the potential application of these two materials as catalysts.

Branched ZnO nanowires have been fabricated on p type Si nanowires by electrodeposition and formed a Si nanowires and ZnO nanowires branched core-shell structure. In these deposition process, Si nanowires could be used as the work electrode for ZnO directly depositing. The morphologies and growth region of ZnO could be controlled by adjusting the applied potential and deposition time. The structural and optical characterizations showed that ZnO nanowires synthesized on Si nanowires have the same physics property as synthesized on other conductive substrates and the optimal condition for ZnO growth. The I-V measurement based on the Si and ZnO p-n heterojunctions showed a typical semiconductor rectification characteristic, and the J-V measurement result indicated energy efficiency was 1.1%.

The multi-target data association method is studied in order to realize multi-target tracking in infrared fish-eye warning system. The Neural Joint Probabilistic Data Association (NJPDA) algorithm is analyzed. It is found that the NJPDA algorithm only considers the distance information between the measurement and the target in the data association process, and its tracking accuracy needs to be further improved. Therefore, a new method fused with direction information is proposed based on the NJPDA algorithm. The proposed algorithm defines the concept of direction difference, introduces the direction information of target motion, and modifies the likelihood function by Gaussian weighting method, so as to fuse the direction information of target motion into the calculation of data interconnection probability. Experimental results demonstrate that the tracking success rate of the proposed algorithm is nearly 10 % higher than that of JPDA and NJPDA algorithms and its consuming time meets the real-time requirement of the infrared fish-eye warning system.