The commercial application of copper bioleaching, an environmentally-friendly approach for low-grade and secondary mineral resources recycling, has increased worldwide since the 2000s. As the world’s second-largest economic entity and the largest developing country, China has the largest demand for metal resources, significantly advancing the theory and industrial technology of copper bioleaching. This paper reviews the exploration and application of copper bioleaching in China. Two typical bioleaching applications and technological processes, bioheap leaching at the Zijinshan Copper Mine and bioheap leaching at the Dexing Copper Mine, are introduced. The considerable research completed by researchers is summarized, especially focusing on the isolation and identification of leaching bacteria, the bioleaching mechanism and interface reactions, multistage percolation behavior, bioleaching system reconstruction, the multiphysics coupled model, and enhanced copper bioleaching from waste printed circuit boards (WPCBs). Based on this investigation in China, key trends and prospects in copper bioleaching—such as efficiency improvement, environmental protection, and improved technology applications—are proposed.

In China, cemented paste backfill (CPB) is a common treatment method after the exploitation of basic energy. The homogeneity of slurry influences the performance of CPB. However, the online monitoring and characterization of homogeneity lack relevant technologies and unified standards. This article discusses an online image analysis technique applied to the online monitoring of cemented paste backfill mixing, which is based on the evolution of the texture of images taken at the surface of the mixing bed. First, the grayscale distribution of the image obtained by the high-speed camera in the CPB preparation process was analyzed by Matlab and its variance (s²) was solved, and the texture features of the image were analyzed by the variance of grayscale distribution. Then, a homogeneity discriminant model ($c_{st}$) was established. The results show that the variance value of the grayscale distribution of the slurry image increases rapidly at first, then gradually decreases, and becomes stable in the final stage since it turns a constant value. When the s² value tends to be stable, the slurry gradually reaches homogenization, and the discriminant coefficient of paste homogenization based on the homogenization discriminant model reaches 0.05. The homogenization prediction of CPB proves to be consistent with the backfill performance comparison results. The evolution of the texture allows obtaining important information on the evolution of different formulations during mixing, which can be used for intelligent monitoring of CPB preparation process.