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Sodium oleate (NaOl), a collector in diaspore flotation, has been widely used for more than 30 years, while its low selectivity becomes an issue under today's process requirement. This study introduced tert dodecyl mercaptan (TDM) together with NaOl as a mixed collector to improve selectivity in diaspore flotation. We found that using the mixed collector of NaOl/TDM (total concentration 0.1 mM, the molar ratio 8:2 of NaOl: TDM) at pH = 9-10 significantly effectively separated diaspore and kaolinite. Comparing the recovery of Al 2 O 3 and the ratio of Al 2 O 3 to SiO 2 (A/S) treated by NaOl/TDM (pH = 9) and NaOl (pH = 10), the Al 2 O 3 recovery and A/S in concentrate for NaOl/TDM are 7.5% and 2.2 higher than that for NaOl in mixed mineral flotation. Also, surface tension measurements, Zeta potential measurements and Fourier Transform Infrared (FTIR) spectra analysis were used to examine its selectivity from a flotation mechanical perspective. Surface tension measurements show that mixed collector NaOl/TDM has stronger surface activity and hydrophobic association than NaOl. The results of Zeta potential measurements and FTIR spectra analysis indicate that NaOl and TDM can selectively co-adsorb diaspore through physical adsorption. Moreover, the adsorption of TDM promotes the adsorption of NaOl on diaspore. However, when NaOl/TDM treats on kaolinite together, TDM can hardly adsorb on mineral surface, nor can it promote the adsorption of NaOl.

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In the field of mineral processing, an accurate image segmentation method is crucial for measuring the size distribution of run-of-mine ore on the conveyor belts in real time0The image-based measurement is considered to be real time, on-line, inexpensive, and non-intrusive. In this paper, a new belt ore image segmentation method was proposed based on a convolutional neural network and image processing technology. It consisted of a classification model and two segmentation algorithms. A total of 2880 images were collected as an original dataset from the process control system (PCS). The test images were processed using the proposed method, the PCS system, the coarse image segmentation (CIS) algorithm, and the fine image segmentation (FIS) algorithm, respectively. The segmentation results of each algorithm were compared with those of the manual segmentation. All empty belt images in the test images were accurately identified by our method. The maximum error between the segmentation results of our method and the results of manual segmentation is 5.61%. The proposed method can accurately identify the empty belt images and segment the coarse material images and mixed material images with high accuracy. Notably, it can be used as a brand new algorithm for belt ore image processing.

Aerodynamic Drum Magnetic Separator (ADMS) uses an adjustable air flow to enhance the separation of magnetic particles from gangue. In order to explore the matching relationship between the magnetic field, the flow field, and the gravity field, as well as the capture and separation behavior of particles under the action of multi-physics, a related simulation model is established using the finite element software COMSOL Multiphysics and the accuracy of the simulation results is verified by measurement, formula calculation, and magnetic separation experiment. The trajectories and capture probabilities of particles in different magnetic fields and flow fields are calculated, as well as the critical airflow velocity corresponding to a specific capture probability. In addition, the magnetic field characteristics and particle capture effect of N-S alternate arrangement and N-N homopolar arrangement are compared by optimizing the permutation of magnetic poles. This model may provide a reference for the accurate control of magnetic separation enhanced by a coupling force field.