CuS and Cu_1.8S have been investigated respectively as anodes of lithium-ion batteries because of their abundant resources, no environment pollution, good electrical conductivity, and a stable discharge voltage plateau. In this work, CuS/Cu_1.8S nanocomposites were firstly prepared simultaneously by the one-pot synthesis method at a relatively higher reaction temperature 200 °C. The CuS/Cu_1.8S nanocomposites anodes exhibited a high initial discharge capacity, an excellent reversible rate capability, and remarkable cycle stability at a high current density, which could be due to the nano-size of the CuS/Cu_1.8S nanocomposites and the assistance of Cu_1.8S. The high electrochemical performance of the CuS/Cu_1.8S nanocomposites indicated that the Cu_xS nanomaterials will be a potential lithium-ion battery anode.

Nondestructive and noninvasive visualization and quantification of soil wetted bodies (SWBs) is of great significance to the development of water-saving agriculture. Unfortunately, measuring the parameters of SWBs is difficult due to the invisibility of SWBs buried underneath the ground and the non-variability of the soil moisture under partial irrigation conditions. Therefore, we performed a laboratory experiment to investigate what SWB attributes can be detected by a GPR. In the laboratory, three typical partial irrigation experiments were conducted to collect the GPR data of SWBs of different sizes, shapes, and burial depths. Additionally, numerical simulation scenarios were designed according to the laboratory experiment. Then, the simulated and measured GPR data were processed by the FK migration method. Based on the simulation, a calibration model for the width of SWBs was constructed. We found that SWB attributes, such as type and location can be obtained from raw radargrams owing to the obvious reflection of the top and bottom interfaces. The results showed that estimating the depth and thickness of SWBs from FK migration radargrams is more reliable than from raw radargrams. Moreover, estimation of the width of SWBs relies on the FK migration radargrams. Our findings indicate that the size and depth of SWBs dominate the width detection accuracy, and the estimated width gained via the width calibration model is improved. Our results highlight the potential for using GPR data to detect SWBs, as well as the potential of using numerical simulation, FK migration, and calibration modeling in combination to extract the size information of SWBs from GPR radargrams.