Molecular dynamics of the interaction between four metal oxides (ZnO, Fe₂O₃, Al₂O₃, and CaO) present in zinc-bearing dust sludge and choline chloride (ChCl)-malonic acid (MA)(1:2) was studied in this work using Materials Studio software. The interaction mechanism was revealed by analyzing the interaction energy and radial distribution function from the perspective of quantum mechanics, and the simulation results were verified by single factor leaching experiments. The calculation results show that the complete cleavage surface of the four metal oxides is the (001) surface, and ChCl-2MA forms a stable structure with multiple intermolecular hydrogen bonds centered on the chlorine atom. The dynamic simulation of the interaction model shows that strength of interaction between ChCl-2MA and the four metal oxides follows the order: ZnO > Fe₂O₃ > Al₂O₃ > CaO. ChCl-2MA mainly interacts with ZnO by chemical adsorption, while ChCl-2MA mainly interacts with Fe₂O₃, Al₂O₃, and CaO by physical adsorption. The radial distribution function shows that Cl in ChCl-2MA and C=O in MA form chemical bonds with Zn in ZnO, and the choline cation (Ch⁺) forms C-H···O with ZnO. Among these bonds, the Cl-Zn bond energy is stronger. During the interaction between ChCl-2MA and Fe₂O₃ and Al₂O₃, O-H···O and C-H···O are formed and interact with CaO by van der Waals force. Single factor leaching experiments show that, under the same leaching conditions, the leaching rate of ZnO by ChCl-2MA is greater than 90%, while the leaching rate of Fe₂O₃, Al₂O₃, and CaO is about 10%. These results indicate good selectivity of ChCl-2MA for ZnO in the zinc-bearing dust sludge. The above conclusions have important theoretical significance and provide an in-depth understanding of the leaching mechanisms of zinc-bearing dust sludge in deep eutectic solvents.

In order to improve the calculation efficiency of a discrete element EDEM (Discrete Element Method) numerical simulation software for micron particles, the particle model is linearly enlarged. At the same time, the parameters of the amplified particles were calibrated according to the Hertz-Mindlin with JKR (Johnson-Kendall-Roberts) contact model to make the amplified particles have the same particle flow characteristics as the actual particles. Actual tests were utilized to gather the angle of repose of the microfine iron tailings, which was then used as a reference value for response surface studies based on the JKR contact model from six factors connected to the fine iron tailings particles. The Plackett-Burman test was used to identify three parameters that had a significant effect on the rest angle: static friction factor; rolling friction factor; and JKR surface energy. The Box-Behnken experiment was used to establish a second-order regression model of the rest angle, and the significant parameters and the optimized parameters were: surface energy JKR coefficient 0.459; particle-particle static friction coefficient 0.393; and particle-particle dynamic friction coefficient 0.393, with a dynamic friction coefficient between particles of 0.106. By entering the parameters into the discrete element program, the angle of repose generated from the simulations was compared with the real test values, and the error was 1.56%. The contact parameters obtained can be used in the discrete element simulation of the amplified particles of fine-grained iron tailings, providing an EDEM model reference for the numerical simulation of fine-grained iron tailings particles. There is no discernible difference between the actual and simulated angles.

A choline chloride-urea (ChCl-urea) deep eutectic solvent (DES) was used to experimentally investigate the secondary recovery of zinc from zinc-bearing dust sludge via a leaching process. The effects of varying the liquid–solid ratio, leaching temperature, stirring speed, and leaching time on the zinc leaching efficiency were determined, and the optimum values of these parameters were found to be 15:1, 90 °C, 400 rpm, and 600 min, respectively, at which a leaching efficiency of 86.87% was achieved. XRF and EDS analyses confirmed that the zinc content in the sludge decreased noticeably after leaching, while those of other elements did not, indicating the selective and efficient leaching of zinc. A study of the leaching kinetics showed that the reaction conforms to the nuclear shrinkage model without solid product layer formation, and the calculated apparent activation energy is 22.16 kJ/mol.

To improve the concentration performance of the concentrator in the iron ore beneficiation process for iron ore tailings, a coupled simulation analysis of the concentration process was conducted using the discrete element software EDEM (Engineering Discrete Element Method) and the finite element FLUENT software. The volume concentration at the bottom flow outlet of the concentrator was used as the evaluation index. The scraper rotation speed, feed rate, and feed concentration were considered as parameters. Response surface experiments were designed using the Box-Behnken module in Design Expert11 software, and numerical simulations were performed to obtain data. Based on the numerical simulation results, a prediction model was established using the backpropagation neural network (backpropagation neural network, BP-NN) and combined with the genetic algorithm (genetic algorithm, GA) for parameter optimization of the thickener’s concentration conditions. The results showed that with a scraper rotation speed of 9.7677 rpm, feed rate of 0.2037 m/s, and feed concentration of 6.5268%, the maximum outlet volume concentration reached approximately 62.00%. The predicted optimal working conditions were validated through physical tests and numerical simulations. The average outlet volume concentration in the physical tests was 60.712% (n = 10) (“n” is the number of experiments), with an error of only 2.077% compared to the predicted value. The middle outlet volume concentration in the numerical simulation experiments was 59.951% (n = 10), with an error of only 3.304% from the expected value. These results demonstrate the feasibility of using a genetic neural network for optimizing the EDEM–FLUENT simulation parameters of the thickener, providing valuable insights for the matching optimization of the thickener’s process parameters.

The most efficient method for recovering microfine-grained hematite ore is flocculation flotation. Because the flocculation–bubble mineralization process in flocculation flotation has yet to be well investigated, a series of experimental investigations on hematite flocculation–bubble were conducted to better understand the hematite flocculation–bubble interaction process. The results show that as the flocculant size increases, the sliding time of the flocculant to the bottom of the bubble shortens, and the change in the instantaneous dynamic velocity is slower when the diameter of the fixed bead is 544.52 μm, which is more favorable to flocculant adhesion on the bubble surface. When the bubble diameter is 544.52 μm and the floc diameter is 39.65 μm, the shortest time is 49.5 ms, and the maximum value of instantaneous velocity is 28.67 μm·ms⁻¹. According to the force analysis of the floc on the bubble surface, when the particle size of the floc is 39.65 μm and the bubble diameter is 544.52 μm, the desorption force is 4.99 × 10⁻³ mN·m⁻¹ larger, and the adhesion force is 7.08 × 10⁻⁴ mN·m⁻¹ smaller. The smaller Bond constant Bo′ is 0.14. In that moment, the flocs in the sodium solution are very stable.